idx int64 1 56k | question stringlengths 15 155 | answer stringlengths 2 29.2k ⌀ | question_cut stringlengths 15 100 | answer_cut stringlengths 2 200 ⌀ | conversation stringlengths 47 29.3k | conversation_cut stringlengths 47 301 |
|---|---|---|---|---|---|---|
5,501 | Understanding regressions - the role of the model | The other side of the answer, complementary to mpiktas's answer but not mentioned so far, is:
"They don't, but as soon as they assume some model structure, they can check it against the data".
The two basic things that could go wrong are: The form of the function, e.g. it's not even linear in logs. So you'd start b... | Understanding regressions - the role of the model | The other side of the answer, complementary to mpiktas's answer but not mentioned so far, is:
"They don't, but as soon as they assume some model structure, they can check it against the data".
The t | Understanding regressions - the role of the model
The other side of the answer, complementary to mpiktas's answer but not mentioned so far, is:
"They don't, but as soon as they assume some model structure, they can check it against the data".
The two basic things that could go wrong are: The form of the function, e.... | Understanding regressions - the role of the model
The other side of the answer, complementary to mpiktas's answer but not mentioned so far, is:
"They don't, but as soon as they assume some model structure, they can check it against the data".
The t |
5,502 | Understanding regressions - the role of the model | An excellent first question! I agree with mpiktas's answer, i.e. the short answer is "they don't, but they hope to have an approximation to the right model that gives approximately the right answer".
In the jargon of epidemiology, this model uncertainty is one source of what's known as 'residual confounding'. See Stev... | Understanding regressions - the role of the model | An excellent first question! I agree with mpiktas's answer, i.e. the short answer is "they don't, but they hope to have an approximation to the right model that gives approximately the right answer". | Understanding regressions - the role of the model
An excellent first question! I agree with mpiktas's answer, i.e. the short answer is "they don't, but they hope to have an approximation to the right model that gives approximately the right answer".
In the jargon of epidemiology, this model uncertainty is one source o... | Understanding regressions - the role of the model
An excellent first question! I agree with mpiktas's answer, i.e. the short answer is "they don't, but they hope to have an approximation to the right model that gives approximately the right answer". |
5,503 | Understanding regressions - the role of the model | There is the famous quote "Essentially, all models are wrong, but some are useful" of George Box. When fitting models like this, we try to (or should) think about the data generation process and the physical, real world, relationships between the response and covariates. We try to express these relationships in a model... | Understanding regressions - the role of the model | There is the famous quote "Essentially, all models are wrong, but some are useful" of George Box. When fitting models like this, we try to (or should) think about the data generation process and the p | Understanding regressions - the role of the model
There is the famous quote "Essentially, all models are wrong, but some are useful" of George Box. When fitting models like this, we try to (or should) think about the data generation process and the physical, real world, relationships between the response and covariates... | Understanding regressions - the role of the model
There is the famous quote "Essentially, all models are wrong, but some are useful" of George Box. When fitting models like this, we try to (or should) think about the data generation process and the p |
5,504 | Understanding regressions - the role of the model | The answers you have already gotten are excellent ones, but I'm going to give a (hopefully) complementary answer from the perspective of an Epidemiologist. I really have three thoughts on this:
First, they don't. See also: All models are wrong, some models are useful. The goal is not to produce a single, definitive num... | Understanding regressions - the role of the model | The answers you have already gotten are excellent ones, but I'm going to give a (hopefully) complementary answer from the perspective of an Epidemiologist. I really have three thoughts on this:
First, | Understanding regressions - the role of the model
The answers you have already gotten are excellent ones, but I'm going to give a (hopefully) complementary answer from the perspective of an Epidemiologist. I really have three thoughts on this:
First, they don't. See also: All models are wrong, some models are useful. T... | Understanding regressions - the role of the model
The answers you have already gotten are excellent ones, but I'm going to give a (hopefully) complementary answer from the perspective of an Epidemiologist. I really have three thoughts on this:
First, |
5,505 | Is it valid to include a baseline measure as control variable when testing the effect of an independent variable on change scores? | To answer your literal question, "Is it valid to include a baseline measure as control variable when testing the effect of an independent variable on change scores?", the answer is no. The answer is no, because by construction the baseline score is correlated with the error term when the change score is used as the dep... | Is it valid to include a baseline measure as control variable when testing the effect of an independ | To answer your literal question, "Is it valid to include a baseline measure as control variable when testing the effect of an independent variable on change scores?", the answer is no. The answer is n | Is it valid to include a baseline measure as control variable when testing the effect of an independent variable on change scores?
To answer your literal question, "Is it valid to include a baseline measure as control variable when testing the effect of an independent variable on change scores?", the answer is no. The ... | Is it valid to include a baseline measure as control variable when testing the effect of an independ
To answer your literal question, "Is it valid to include a baseline measure as control variable when testing the effect of an independent variable on change scores?", the answer is no. The answer is n |
5,506 | Is it valid to include a baseline measure as control variable when testing the effect of an independent variable on change scores? | Andy's answer seems to be the economist's view of things. It is accepted practice in clinical trials to almost always adjust for the baseline version of the response variable, to greatly increase power. Since we condition on the baseline variables there is no 'error term' for them to be confused with the overall erro... | Is it valid to include a baseline measure as control variable when testing the effect of an independ | Andy's answer seems to be the economist's view of things. It is accepted practice in clinical trials to almost always adjust for the baseline version of the response variable, to greatly increase pow | Is it valid to include a baseline measure as control variable when testing the effect of an independent variable on change scores?
Andy's answer seems to be the economist's view of things. It is accepted practice in clinical trials to almost always adjust for the baseline version of the response variable, to greatly i... | Is it valid to include a baseline measure as control variable when testing the effect of an independ
Andy's answer seems to be the economist's view of things. It is accepted practice in clinical trials to almost always adjust for the baseline version of the response variable, to greatly increase pow |
5,507 | Is it valid to include a baseline measure as control variable when testing the effect of an independent variable on change scores? | EDIT: Andy W's argument convinced me to drop Model C. I added another possibility: Analyzing change with Random Coefficient Models (aka Multilevel Models or Mixed Effect Models
There has been a lot of scientific debate about the use of difference scores. My favorite texts are Rogosa (1982, [1]) and Fitzmaurice, Laird, ... | Is it valid to include a baseline measure as control variable when testing the effect of an independ | EDIT: Andy W's argument convinced me to drop Model C. I added another possibility: Analyzing change with Random Coefficient Models (aka Multilevel Models or Mixed Effect Models
There has been a lot of | Is it valid to include a baseline measure as control variable when testing the effect of an independent variable on change scores?
EDIT: Andy W's argument convinced me to drop Model C. I added another possibility: Analyzing change with Random Coefficient Models (aka Multilevel Models or Mixed Effect Models
There has be... | Is it valid to include a baseline measure as control variable when testing the effect of an independ
EDIT: Andy W's argument convinced me to drop Model C. I added another possibility: Analyzing change with Random Coefficient Models (aka Multilevel Models or Mixed Effect Models
There has been a lot of |
5,508 | Is it valid to include a baseline measure as control variable when testing the effect of an independent variable on change scores? | We can alter @ocram's reasoning slightly to have
$$\begin{align*} \text{E}[w_1 - w_0 \mid X, w_0] &= \beta_0 + x \beta + w_0 \gamma \\
\text{E}[w_1 \mid X, w_0] &= \beta_0 + x \beta + w_0 (\gamma + 1) \end{align*} $$
So, if this is the right model, saying that the difference depends upon the weight implies that the en... | Is it valid to include a baseline measure as control variable when testing the effect of an independ | We can alter @ocram's reasoning slightly to have
$$\begin{align*} \text{E}[w_1 - w_0 \mid X, w_0] &= \beta_0 + x \beta + w_0 \gamma \\
\text{E}[w_1 \mid X, w_0] &= \beta_0 + x \beta + w_0 (\gamma + 1 | Is it valid to include a baseline measure as control variable when testing the effect of an independent variable on change scores?
We can alter @ocram's reasoning slightly to have
$$\begin{align*} \text{E}[w_1 - w_0 \mid X, w_0] &= \beta_0 + x \beta + w_0 \gamma \\
\text{E}[w_1 \mid X, w_0] &= \beta_0 + x \beta + w_0 ... | Is it valid to include a baseline measure as control variable when testing the effect of an independ
We can alter @ocram's reasoning slightly to have
$$\begin{align*} \text{E}[w_1 - w_0 \mid X, w_0] &= \beta_0 + x \beta + w_0 \gamma \\
\text{E}[w_1 \mid X, w_0] &= \beta_0 + x \beta + w_0 (\gamma + 1 |
5,509 | Is it valid to include a baseline measure as control variable when testing the effect of an independent variable on change scores? | Glymour et al. (2005) addressed using baseline adjustment when analyzing a change score. If change in health status preceded baseline assessment or there is large measurement error in the dependent variable, they find that a bias can arise if the regression model using change score as the dependent variable includes a... | Is it valid to include a baseline measure as control variable when testing the effect of an independ | Glymour et al. (2005) addressed using baseline adjustment when analyzing a change score. If change in health status preceded baseline assessment or there is large measurement error in the dependent va | Is it valid to include a baseline measure as control variable when testing the effect of an independent variable on change scores?
Glymour et al. (2005) addressed using baseline adjustment when analyzing a change score. If change in health status preceded baseline assessment or there is large measurement error in the d... | Is it valid to include a baseline measure as control variable when testing the effect of an independ
Glymour et al. (2005) addressed using baseline adjustment when analyzing a change score. If change in health status preceded baseline assessment or there is large measurement error in the dependent va |
5,510 | Is it valid to include a baseline measure as control variable when testing the effect of an independent variable on change scores? | See Josh Angrist on exactly this question: http://www.mostlyharmlesseconometrics.com/2009/10/adding-lagged-dependent-vars-to-differenced-models/. He comes down largely against including the lagged DV in your model. There is nothing in his response that is not in the responses above, but a further succinct answer to y... | Is it valid to include a baseline measure as control variable when testing the effect of an independ | See Josh Angrist on exactly this question: http://www.mostlyharmlesseconometrics.com/2009/10/adding-lagged-dependent-vars-to-differenced-models/. He comes down largely against including the lagged DV | Is it valid to include a baseline measure as control variable when testing the effect of an independent variable on change scores?
See Josh Angrist on exactly this question: http://www.mostlyharmlesseconometrics.com/2009/10/adding-lagged-dependent-vars-to-differenced-models/. He comes down largely against including th... | Is it valid to include a baseline measure as control variable when testing the effect of an independ
See Josh Angrist on exactly this question: http://www.mostlyharmlesseconometrics.com/2009/10/adding-lagged-dependent-vars-to-differenced-models/. He comes down largely against including the lagged DV |
5,511 | Is it valid to include a baseline measure as control variable when testing the effect of an independent variable on change scores? | Ocram is not correct. The difference in weights does not take the initial weight into account. Specifically, the intial weight is kind of taken out by subtracting the end weight from it.
Therefore, I would argue that it does not violate any assumptions if you control for the initial weight.
(The same logic applies if ... | Is it valid to include a baseline measure as control variable when testing the effect of an independ | Ocram is not correct. The difference in weights does not take the initial weight into account. Specifically, the intial weight is kind of taken out by subtracting the end weight from it.
Therefore, I | Is it valid to include a baseline measure as control variable when testing the effect of an independent variable on change scores?
Ocram is not correct. The difference in weights does not take the initial weight into account. Specifically, the intial weight is kind of taken out by subtracting the end weight from it.
Th... | Is it valid to include a baseline measure as control variable when testing the effect of an independ
Ocram is not correct. The difference in weights does not take the initial weight into account. Specifically, the intial weight is kind of taken out by subtracting the end weight from it.
Therefore, I |
5,512 | Is it valid to include a baseline measure as control variable when testing the effect of an independent variable on change scores? | Just an addition to the entire discussion (I did not know where to put a comment, so I put it as an answer): if you plan to do a longitudinal analysis in the pharmaceutical industry, then the adjustment for baseline is mentioned by the major guidelines (FDA and EMA) also in case of the analysis of change (change score)... | Is it valid to include a baseline measure as control variable when testing the effect of an independ | Just an addition to the entire discussion (I did not know where to put a comment, so I put it as an answer): if you plan to do a longitudinal analysis in the pharmaceutical industry, then the adjustme | Is it valid to include a baseline measure as control variable when testing the effect of an independent variable on change scores?
Just an addition to the entire discussion (I did not know where to put a comment, so I put it as an answer): if you plan to do a longitudinal analysis in the pharmaceutical industry, then t... | Is it valid to include a baseline measure as control variable when testing the effect of an independ
Just an addition to the entire discussion (I did not know where to put a comment, so I put it as an answer): if you plan to do a longitudinal analysis in the pharmaceutical industry, then the adjustme |
5,513 | Is it valid to include a baseline measure as control variable when testing the effect of an independent variable on change scores? | Observe that
$\underbrace{\textrm{end weight} - \textrm{initial weight}}_{Y} = \beta_{0} + \beta^{T}x$
is equivalent to
$\textrm{end weight} = \textrm{initial weight} + \beta_{0} + \beta^{T}x$
In words, using the change in weight (instead of the end weight itself) as DV already accounts for the initial weight. | Is it valid to include a baseline measure as control variable when testing the effect of an independ | Observe that
$\underbrace{\textrm{end weight} - \textrm{initial weight}}_{Y} = \beta_{0} + \beta^{T}x$
is equivalent to
$\textrm{end weight} = \textrm{initial weight} + \beta_{0} + \beta^{T}x$
In wor | Is it valid to include a baseline measure as control variable when testing the effect of an independent variable on change scores?
Observe that
$\underbrace{\textrm{end weight} - \textrm{initial weight}}_{Y} = \beta_{0} + \beta^{T}x$
is equivalent to
$\textrm{end weight} = \textrm{initial weight} + \beta_{0} + \beta^{... | Is it valid to include a baseline measure as control variable when testing the effect of an independ
Observe that
$\underbrace{\textrm{end weight} - \textrm{initial weight}}_{Y} = \beta_{0} + \beta^{T}x$
is equivalent to
$\textrm{end weight} = \textrm{initial weight} + \beta_{0} + \beta^{T}x$
In wor |
5,514 | How to interpret mean of Silhouette plot? | Sergey's answer contains the critical point, which is that the silhouette coefficient quantifies the quality of clustering achieved -- so you should select the number of clusters that maximizes the silhouette coefficient.
The long answer is that the best way to evaluate the results of your clustering efforts is to st... | How to interpret mean of Silhouette plot? | Sergey's answer contains the critical point, which is that the silhouette coefficient quantifies the quality of clustering achieved -- so you should select the number of clusters that maximizes the si | How to interpret mean of Silhouette plot?
Sergey's answer contains the critical point, which is that the silhouette coefficient quantifies the quality of clustering achieved -- so you should select the number of clusters that maximizes the silhouette coefficient.
The long answer is that the best way to evaluate the r... | How to interpret mean of Silhouette plot?
Sergey's answer contains the critical point, which is that the silhouette coefficient quantifies the quality of clustering achieved -- so you should select the number of clusters that maximizes the si |
5,515 | How to interpret mean of Silhouette plot? | I have been looking into the same thing today and found an interpretation here. It makes logical sense but I am not sure if we can blindly apply the interpretation for our datasets. In summary, what that article says is the following:
0.71-1.0
A strong structure has been found
0.51-0.70
A reasonable structure has been... | How to interpret mean of Silhouette plot? | I have been looking into the same thing today and found an interpretation here. It makes logical sense but I am not sure if we can blindly apply the interpretation for our datasets. In summary, what t | How to interpret mean of Silhouette plot?
I have been looking into the same thing today and found an interpretation here. It makes logical sense but I am not sure if we can blindly apply the interpretation for our datasets. In summary, what that article says is the following:
0.71-1.0
A strong structure has been found
... | How to interpret mean of Silhouette plot?
I have been looking into the same thing today and found an interpretation here. It makes logical sense but I am not sure if we can blindly apply the interpretation for our datasets. In summary, what t |
5,516 | How to interpret mean of Silhouette plot? | Take a look at the
Cluster Validity Analysis Platform (CVAP) ToolBox
And some of the materials (links) from CVAP:
Silhouette index (overall average
silhouette) a larger Silhouette value
indicates a better quality of a
clustering result [Chen et al. 2002]
N. Bolshakova, F. Azuaje. 2003. Cluster validation tech... | How to interpret mean of Silhouette plot? | Take a look at the
Cluster Validity Analysis Platform (CVAP) ToolBox
And some of the materials (links) from CVAP:
Silhouette index (overall average
silhouette) a larger Silhouette value
indicate | How to interpret mean of Silhouette plot?
Take a look at the
Cluster Validity Analysis Platform (CVAP) ToolBox
And some of the materials (links) from CVAP:
Silhouette index (overall average
silhouette) a larger Silhouette value
indicates a better quality of a
clustering result [Chen et al. 2002]
N. Bolshakova... | How to interpret mean of Silhouette plot?
Take a look at the
Cluster Validity Analysis Platform (CVAP) ToolBox
And some of the materials (links) from CVAP:
Silhouette index (overall average
silhouette) a larger Silhouette value
indicate |
5,517 | How to interpret mean of Silhouette plot? | If you are trying to select the number of clusters for unsupervised learning then maybe you could try doing something like-
http://scikit-learn.org/stable/auto_examples/cluster/plot_kmeans_silhouette_analysis.html
They use more than just the silhouette score mean (they use the distribution) but it makes sense. It seem... | How to interpret mean of Silhouette plot? | If you are trying to select the number of clusters for unsupervised learning then maybe you could try doing something like-
http://scikit-learn.org/stable/auto_examples/cluster/plot_kmeans_silhouette_ | How to interpret mean of Silhouette plot?
If you are trying to select the number of clusters for unsupervised learning then maybe you could try doing something like-
http://scikit-learn.org/stable/auto_examples/cluster/plot_kmeans_silhouette_analysis.html
They use more than just the silhouette score mean (they use the... | How to interpret mean of Silhouette plot?
If you are trying to select the number of clusters for unsupervised learning then maybe you could try doing something like-
http://scikit-learn.org/stable/auto_examples/cluster/plot_kmeans_silhouette_ |
5,518 | Does the beta distribution have a conjugate prior? | It seems that you already gave up on conjugacy. Just for the record, one thing that I've seen people doing (but don't remember exactly where, sorry) is a reparameterization like this. If $X_1,\dots,X_n$ are conditionally iid, given $\alpha,\beta$, such that $X_i\mid\alpha,\beta\sim\mathrm{Beta}(\alpha,\beta)$, remember... | Does the beta distribution have a conjugate prior? | It seems that you already gave up on conjugacy. Just for the record, one thing that I've seen people doing (but don't remember exactly where, sorry) is a reparameterization like this. If $X_1,\dots,X_ | Does the beta distribution have a conjugate prior?
It seems that you already gave up on conjugacy. Just for the record, one thing that I've seen people doing (but don't remember exactly where, sorry) is a reparameterization like this. If $X_1,\dots,X_n$ are conditionally iid, given $\alpha,\beta$, such that $X_i\mid\al... | Does the beta distribution have a conjugate prior?
It seems that you already gave up on conjugacy. Just for the record, one thing that I've seen people doing (but don't remember exactly where, sorry) is a reparameterization like this. If $X_1,\dots,X_ |
5,519 | Does the beta distribution have a conjugate prior? | Yes, it has a conjugate prior in the exponential family. Consider the three parameter family
$$
\pi(\alpha, \beta \mid a, b, p)
\propto \left\{\frac{\Gamma(\alpha + \beta)}{\Gamma(\alpha)\Gamma(\beta)}\right\}^p
\exp\left(a\alpha + b\beta \right).
$$
For some values of $(a, b, p)$, this is integrable, although I ... | Does the beta distribution have a conjugate prior? | Yes, it has a conjugate prior in the exponential family. Consider the three parameter family
$$
\pi(\alpha, \beta \mid a, b, p)
\propto \left\{\frac{\Gamma(\alpha + \beta)}{\Gamma(\alpha)\Gamma(\beta | Does the beta distribution have a conjugate prior?
Yes, it has a conjugate prior in the exponential family. Consider the three parameter family
$$
\pi(\alpha, \beta \mid a, b, p)
\propto \left\{\frac{\Gamma(\alpha + \beta)}{\Gamma(\alpha)\Gamma(\beta)}\right\}^p
\exp\left(a\alpha + b\beta \right).
$$
For some val... | Does the beta distribution have a conjugate prior?
Yes, it has a conjugate prior in the exponential family. Consider the three parameter family
$$
\pi(\alpha, \beta \mid a, b, p)
\propto \left\{\frac{\Gamma(\alpha + \beta)}{\Gamma(\alpha)\Gamma(\beta |
5,520 | Does the beta distribution have a conjugate prior? | In theory there should be a conjugate prior for the beta distribution. This is because
the beta distribution is one of the exponential family distributions, and
in theory it should be possible to derive a prior. See, e.g., wikipedia, D Blei's lecture on exponential families.
However the derivation looks difficult, an... | Does the beta distribution have a conjugate prior? | In theory there should be a conjugate prior for the beta distribution. This is because
the beta distribution is one of the exponential family distributions, and
in theory it should be possible to der | Does the beta distribution have a conjugate prior?
In theory there should be a conjugate prior for the beta distribution. This is because
the beta distribution is one of the exponential family distributions, and
in theory it should be possible to derive a prior. See, e.g., wikipedia, D Blei's lecture on exponential fa... | Does the beta distribution have a conjugate prior?
In theory there should be a conjugate prior for the beta distribution. This is because
the beta distribution is one of the exponential family distributions, and
in theory it should be possible to der |
5,521 | Does the beta distribution have a conjugate prior? | Robert and Casella (RC) happen to describe the family of conjugate priors of the beta distribution in Example 3.6 (p 71 - 75) of their book, Introducing Monte Carlo Methods in R, Springer, 2010. However, they quote the result without citing a source.
Added in response to gung's request for details. RC state that for di... | Does the beta distribution have a conjugate prior? | Robert and Casella (RC) happen to describe the family of conjugate priors of the beta distribution in Example 3.6 (p 71 - 75) of their book, Introducing Monte Carlo Methods in R, Springer, 2010. Howev | Does the beta distribution have a conjugate prior?
Robert and Casella (RC) happen to describe the family of conjugate priors of the beta distribution in Example 3.6 (p 71 - 75) of their book, Introducing Monte Carlo Methods in R, Springer, 2010. However, they quote the result without citing a source.
Added in response ... | Does the beta distribution have a conjugate prior?
Robert and Casella (RC) happen to describe the family of conjugate priors of the beta distribution in Example 3.6 (p 71 - 75) of their book, Introducing Monte Carlo Methods in R, Springer, 2010. Howev |
5,522 | Does the beta distribution have a conjugate prior? | I do not believe there is a "standard" (i.e., exponential family) distribution that is the conjugate prior for the beta distribution. However, if one does exist it would have to be a bivariate distribution. | Does the beta distribution have a conjugate prior? | I do not believe there is a "standard" (i.e., exponential family) distribution that is the conjugate prior for the beta distribution. However, if one does exist it would have to be a bivariate distri | Does the beta distribution have a conjugate prior?
I do not believe there is a "standard" (i.e., exponential family) distribution that is the conjugate prior for the beta distribution. However, if one does exist it would have to be a bivariate distribution. | Does the beta distribution have a conjugate prior?
I do not believe there is a "standard" (i.e., exponential family) distribution that is the conjugate prior for the beta distribution. However, if one does exist it would have to be a bivariate distri |
5,523 | Lift measure in data mining | I'll give an example of how "lift" is useful...
Imagine you are running a direct mail campaign where you mail customers an offer in the hopes they respond. Historical data shows that when you mail your customer base completely at random about 8% of them respond to the mailing (i.e. they come in and shop with the offer)... | Lift measure in data mining | I'll give an example of how "lift" is useful...
Imagine you are running a direct mail campaign where you mail customers an offer in the hopes they respond. Historical data shows that when you mail you | Lift measure in data mining
I'll give an example of how "lift" is useful...
Imagine you are running a direct mail campaign where you mail customers an offer in the hopes they respond. Historical data shows that when you mail your customer base completely at random about 8% of them respond to the mailing (i.e. they come... | Lift measure in data mining
I'll give an example of how "lift" is useful...
Imagine you are running a direct mail campaign where you mail customers an offer in the hopes they respond. Historical data shows that when you mail you |
5,524 | Lift measure in data mining | Lift charts represent the ratio between the response of a model vs the absence of that model. Typically, it's represented by the percentage of cases in the X and the number of times the response is better in the Y axe. For example, a model with lift=2 at the point 10% means:
Without any model taking a 10% of the popul... | Lift measure in data mining | Lift charts represent the ratio between the response of a model vs the absence of that model. Typically, it's represented by the percentage of cases in the X and the number of times the response is be | Lift measure in data mining
Lift charts represent the ratio between the response of a model vs the absence of that model. Typically, it's represented by the percentage of cases in the X and the number of times the response is better in the Y axe. For example, a model with lift=2 at the point 10% means:
Without any mod... | Lift measure in data mining
Lift charts represent the ratio between the response of a model vs the absence of that model. Typically, it's represented by the percentage of cases in the X and the number of times the response is be |
5,525 | Lift measure in data mining | Lift is nothing but the ratio of Confidence to Expected Confidence. In the area of association rules - "A lift ratio larger than 1.0 implies that the relationship between the antecedent and the consequent is more significant than would be expected if the two sets were independent. The larger the lift ratio, the more s... | Lift measure in data mining | Lift is nothing but the ratio of Confidence to Expected Confidence. In the area of association rules - "A lift ratio larger than 1.0 implies that the relationship between the antecedent and the conse | Lift measure in data mining
Lift is nothing but the ratio of Confidence to Expected Confidence. In the area of association rules - "A lift ratio larger than 1.0 implies that the relationship between the antecedent and the consequent is more significant than would be expected if the two sets were independent. The large... | Lift measure in data mining
Lift is nothing but the ratio of Confidence to Expected Confidence. In the area of association rules - "A lift ratio larger than 1.0 implies that the relationship between the antecedent and the conse |
5,526 | Lift measure in data mining | Lift is just a measure to measure the importance of the rule
its a measure to check whether this rule is in the list by random chance or we are expecting
Lift = Confidence / Expected Confidence | Lift measure in data mining | Lift is just a measure to measure the importance of the rule
its a measure to check whether this rule is in the list by random chance or we are expecting
Lift = Confidence / Expected Confidence | Lift measure in data mining
Lift is just a measure to measure the importance of the rule
its a measure to check whether this rule is in the list by random chance or we are expecting
Lift = Confidence / Expected Confidence | Lift measure in data mining
Lift is just a measure to measure the importance of the rule
its a measure to check whether this rule is in the list by random chance or we are expecting
Lift = Confidence / Expected Confidence |
5,527 | Lift measure in data mining | Say we are using the example of a grocery store that is testing the validity of an association rule that has an antecedent and a consequent (for example: "If a customer buys bread, they will also buy butter").
If you look at all transactions, and examine one at random, the probability that that transaction contains the... | Lift measure in data mining | Say we are using the example of a grocery store that is testing the validity of an association rule that has an antecedent and a consequent (for example: "If a customer buys bread, they will also buy | Lift measure in data mining
Say we are using the example of a grocery store that is testing the validity of an association rule that has an antecedent and a consequent (for example: "If a customer buys bread, they will also buy butter").
If you look at all transactions, and examine one at random, the probability that t... | Lift measure in data mining
Say we are using the example of a grocery store that is testing the validity of an association rule that has an antecedent and a consequent (for example: "If a customer buys bread, they will also buy |
5,528 | Is there an explanation for why there are so many natural phenomena that follow normal distribution? | Let me start by denying the premise. Robert Geary probably didn't overstate the case when he said (in 1947) "...normality is a myth; there never was, and never will be, a normal distribution." --
the normal distribution is a model*, an approximation that is sometimes more-or-less useful.
$\:$*(about which, see George ... | Is there an explanation for why there are so many natural phenomena that follow normal distribution? | Let me start by denying the premise. Robert Geary probably didn't overstate the case when he said (in 1947) "...normality is a myth; there never was, and never will be, a normal distribution." --
the | Is there an explanation for why there are so many natural phenomena that follow normal distribution?
Let me start by denying the premise. Robert Geary probably didn't overstate the case when he said (in 1947) "...normality is a myth; there never was, and never will be, a normal distribution." --
the normal distribution... | Is there an explanation for why there are so many natural phenomena that follow normal distribution?
Let me start by denying the premise. Robert Geary probably didn't overstate the case when he said (in 1947) "...normality is a myth; there never was, and never will be, a normal distribution." --
the |
5,529 | Is there an explanation for why there are so many natural phenomena that follow normal distribution? | There is a famous saying by Gabriel Lippmann (physicist, Nobel laureate), as told by Poincaré:
[The normal distribution] cannot be obtained by rigorous deductions. Several of its putative proofs are awful [...]. Nonetheless,
everyone believes it, as M. Lippmann told me one day, because experimenters imagine it to b... | Is there an explanation for why there are so many natural phenomena that follow normal distribution? | There is a famous saying by Gabriel Lippmann (physicist, Nobel laureate), as told by Poincaré:
[The normal distribution] cannot be obtained by rigorous deductions. Several of its putative proofs are | Is there an explanation for why there are so many natural phenomena that follow normal distribution?
There is a famous saying by Gabriel Lippmann (physicist, Nobel laureate), as told by Poincaré:
[The normal distribution] cannot be obtained by rigorous deductions. Several of its putative proofs are awful [...]. Nonet... | Is there an explanation for why there are so many natural phenomena that follow normal distribution?
There is a famous saying by Gabriel Lippmann (physicist, Nobel laureate), as told by Poincaré:
[The normal distribution] cannot be obtained by rigorous deductions. Several of its putative proofs are |
5,530 | Is there an explanation for why there are so many natural phenomena that follow normal distribution? | What law of physics makes so that so many natural phenomena have
normal distribution? It would seem more intuitive that they would have
uniform distribution.
The normal distribution is a common place in natural sciences. The usual explanation is why it happens in measurement errors is through some form of large nu... | Is there an explanation for why there are so many natural phenomena that follow normal distribution? | What law of physics makes so that so many natural phenomena have
normal distribution? It would seem more intuitive that they would have
uniform distribution.
The normal distribution is a common p | Is there an explanation for why there are so many natural phenomena that follow normal distribution?
What law of physics makes so that so many natural phenomena have
normal distribution? It would seem more intuitive that they would have
uniform distribution.
The normal distribution is a common place in natural sci... | Is there an explanation for why there are so many natural phenomena that follow normal distribution?
What law of physics makes so that so many natural phenomena have
normal distribution? It would seem more intuitive that they would have
uniform distribution.
The normal distribution is a common p |
5,531 | Is there an explanation for why there are so many natural phenomena that follow normal distribution? | there is an awful lot of overly complicated explanations here...
A good way it was related to me is the following:
Roll a single die, and you have an equal likelihood of rolling each number (1-6), and hence, the PDF is constant.
Roll two dice and sum the results together, and the PDF is no longer constant. This is bec... | Is there an explanation for why there are so many natural phenomena that follow normal distribution? | there is an awful lot of overly complicated explanations here...
A good way it was related to me is the following:
Roll a single die, and you have an equal likelihood of rolling each number (1-6), an | Is there an explanation for why there are so many natural phenomena that follow normal distribution?
there is an awful lot of overly complicated explanations here...
A good way it was related to me is the following:
Roll a single die, and you have an equal likelihood of rolling each number (1-6), and hence, the PDF is... | Is there an explanation for why there are so many natural phenomena that follow normal distribution?
there is an awful lot of overly complicated explanations here...
A good way it was related to me is the following:
Roll a single die, and you have an equal likelihood of rolling each number (1-6), an |
5,532 | Is there an explanation for why there are so many natural phenomena that follow normal distribution? | What law of physics makes so that so many natural phenomena have normal distribution?
No idea. On the other hand I've also no idea whether it's true, or indeed what 'so many' means.
However, rearranging the problem a little, there is good reason to assume (that is, to model) a continuous quantity that you believe to h... | Is there an explanation for why there are so many natural phenomena that follow normal distribution? | What law of physics makes so that so many natural phenomena have normal distribution?
No idea. On the other hand I've also no idea whether it's true, or indeed what 'so many' means.
However, rearrang | Is there an explanation for why there are so many natural phenomena that follow normal distribution?
What law of physics makes so that so many natural phenomena have normal distribution?
No idea. On the other hand I've also no idea whether it's true, or indeed what 'so many' means.
However, rearranging the problem a l... | Is there an explanation for why there are so many natural phenomena that follow normal distribution?
What law of physics makes so that so many natural phenomena have normal distribution?
No idea. On the other hand I've also no idea whether it's true, or indeed what 'so many' means.
However, rearrang |
5,533 | Dealing with singular fit in mixed models | When you obtain a singular fit, this is often indicating that the model is overfitted – that is, the random effects structure is too complex to be supported by the data, which naturally leads to the advice to remove the most complex part of the random effects structure (usually random slopes). The benefit of this appr... | Dealing with singular fit in mixed models | When you obtain a singular fit, this is often indicating that the model is overfitted – that is, the random effects structure is too complex to be supported by the data, which naturally leads to the a | Dealing with singular fit in mixed models
When you obtain a singular fit, this is often indicating that the model is overfitted – that is, the random effects structure is too complex to be supported by the data, which naturally leads to the advice to remove the most complex part of the random effects structure (usually... | Dealing with singular fit in mixed models
When you obtain a singular fit, this is often indicating that the model is overfitted – that is, the random effects structure is too complex to be supported by the data, which naturally leads to the a |
5,534 | Dealing with singular fit in mixed models | This is a very interesting thread, with interesting answers and comments! Since this hasn't been brought up yet, I wanted to point out that we have very little data for each subject (as I understand it). Indeed, each subject has only two values for each of the response variable Y, categorical variable Condition and co... | Dealing with singular fit in mixed models | This is a very interesting thread, with interesting answers and comments! Since this hasn't been brought up yet, I wanted to point out that we have very little data for each subject (as I understand i | Dealing with singular fit in mixed models
This is a very interesting thread, with interesting answers and comments! Since this hasn't been brought up yet, I wanted to point out that we have very little data for each subject (as I understand it). Indeed, each subject has only two values for each of the response variabl... | Dealing with singular fit in mixed models
This is a very interesting thread, with interesting answers and comments! Since this hasn't been brought up yet, I wanted to point out that we have very little data for each subject (as I understand i |
5,535 | What is the difference between Metropolis-Hastings, Gibbs, Importance, and Rejection sampling? | As detailed in our book with George Casella, Monte Carlo statistical methods, these methods are used to produce samples from a given distribution, with density $f$ say, either to get an idea about this distribution, or to solve an integration or optimisation problem related with $f$. For instance, to find the value of ... | What is the difference between Metropolis-Hastings, Gibbs, Importance, and Rejection sampling? | As detailed in our book with George Casella, Monte Carlo statistical methods, these methods are used to produce samples from a given distribution, with density $f$ say, either to get an idea about thi | What is the difference between Metropolis-Hastings, Gibbs, Importance, and Rejection sampling?
As detailed in our book with George Casella, Monte Carlo statistical methods, these methods are used to produce samples from a given distribution, with density $f$ say, either to get an idea about this distribution, or to sol... | What is the difference between Metropolis-Hastings, Gibbs, Importance, and Rejection sampling?
As detailed in our book with George Casella, Monte Carlo statistical methods, these methods are used to produce samples from a given distribution, with density $f$ say, either to get an idea about thi |
5,536 | How to sample from a normal distribution with known mean and variance using a conventional programming language? | If you can sample from a given distribution with mean 0 and variance 1, then you can easily sample from a scale-location transformation of that distribution, which has mean $\mu$ and variance $\sigma^2$. If $x$ is a sample from a mean 0 and variance 1 distribution then
$$\sigma x + \mu$$
is a sample with mean $\mu$ an... | How to sample from a normal distribution with known mean and variance using a conventional programmi | If you can sample from a given distribution with mean 0 and variance 1, then you can easily sample from a scale-location transformation of that distribution, which has mean $\mu$ and variance $\sigma^ | How to sample from a normal distribution with known mean and variance using a conventional programming language?
If you can sample from a given distribution with mean 0 and variance 1, then you can easily sample from a scale-location transformation of that distribution, which has mean $\mu$ and variance $\sigma^2$. If ... | How to sample from a normal distribution with known mean and variance using a conventional programmi
If you can sample from a given distribution with mean 0 and variance 1, then you can easily sample from a scale-location transformation of that distribution, which has mean $\mu$ and variance $\sigma^ |
5,537 | How to sample from a normal distribution with known mean and variance using a conventional programming language? | This is really a comment on Michael Lew's answer and Fixee's comment, but is posted as an answer because I don't have the reputation on this site to comment.
The sum of twelve independent random variables uniformly distributed on $[0, 1]$ has mean $6$ and variance $1$. In other words,
$$E\left [\sum_{i=1}^{12} X_i\ri... | How to sample from a normal distribution with known mean and variance using a conventional programmi | This is really a comment on Michael Lew's answer and Fixee's comment, but is posted as an answer because I don't have the reputation on this site to comment.
The sum of twelve independent random varia | How to sample from a normal distribution with known mean and variance using a conventional programming language?
This is really a comment on Michael Lew's answer and Fixee's comment, but is posted as an answer because I don't have the reputation on this site to comment.
The sum of twelve independent random variables un... | How to sample from a normal distribution with known mean and variance using a conventional programmi
This is really a comment on Michael Lew's answer and Fixee's comment, but is posted as an answer because I don't have the reputation on this site to comment.
The sum of twelve independent random varia |
5,538 | How to sample from a normal distribution with known mean and variance using a conventional programming language? | In addition to the answer by NRH, if you still have no means to generate random samples from a "standard normal distribution" N(0,1), below is a good and simple way (since you mention you don't have a statistical package, the functions below should be available in most standard programming languages).
1. Generate u an... | How to sample from a normal distribution with known mean and variance using a conventional programmi | In addition to the answer by NRH, if you still have no means to generate random samples from a "standard normal distribution" N(0,1), below is a good and simple way (since you mention you don't have a | How to sample from a normal distribution with known mean and variance using a conventional programming language?
In addition to the answer by NRH, if you still have no means to generate random samples from a "standard normal distribution" N(0,1), below is a good and simple way (since you mention you don't have a statis... | How to sample from a normal distribution with known mean and variance using a conventional programmi
In addition to the answer by NRH, if you still have no means to generate random samples from a "standard normal distribution" N(0,1), below is a good and simple way (since you mention you don't have a |
5,539 | How to sample from a normal distribution with known mean and variance using a conventional programming language? | The normal distribution emerges when one adds together a lot of random values of similar distribution (similar to each other, I mean). If you add together ten or more uniformly distributed random values then the sum is very nearly normally distributed. (Add more than ten if you want it to be even more normal, but ten i... | How to sample from a normal distribution with known mean and variance using a conventional programmi | The normal distribution emerges when one adds together a lot of random values of similar distribution (similar to each other, I mean). If you add together ten or more uniformly distributed random valu | How to sample from a normal distribution with known mean and variance using a conventional programming language?
The normal distribution emerges when one adds together a lot of random values of similar distribution (similar to each other, I mean). If you add together ten or more uniformly distributed random values then... | How to sample from a normal distribution with known mean and variance using a conventional programmi
The normal distribution emerges when one adds together a lot of random values of similar distribution (similar to each other, I mean). If you add together ten or more uniformly distributed random valu |
5,540 | What is the rationale of the Matérn covariance function? | In addition to @Dahn's nice answer, I thought I would try to say a little bit more about where the Bessel and Gamma functions come from. One starting point for arriving at the covariance function is Bochner's theorem.
Theorem (Bochner) A continuous stationary function $k(x, y) = \widetilde{k}(|x − y|)$ is positive def... | What is the rationale of the Matérn covariance function? | In addition to @Dahn's nice answer, I thought I would try to say a little bit more about where the Bessel and Gamma functions come from. One starting point for arriving at the covariance function is B | What is the rationale of the Matérn covariance function?
In addition to @Dahn's nice answer, I thought I would try to say a little bit more about where the Bessel and Gamma functions come from. One starting point for arriving at the covariance function is Bochner's theorem.
Theorem (Bochner) A continuous stationary fu... | What is the rationale of the Matérn covariance function?
In addition to @Dahn's nice answer, I thought I would try to say a little bit more about where the Bessel and Gamma functions come from. One starting point for arriving at the covariance function is B |
5,541 | What is the rationale of the Matérn covariance function? | I do not know, but I found this question very interesting and here's what I got after a bit of reading on it.
For certain values of $\nu$, the Matérn covariance function can be expressed as a product of an exponential and a polynomial. E.g. for $\nu = 5/2$:
$$C_{5/2}(d) = \sigma^2\left(1 + \frac{\sqrt 5 d}{\rho} + \fra... | What is the rationale of the Matérn covariance function? | I do not know, but I found this question very interesting and here's what I got after a bit of reading on it.
For certain values of $\nu$, the Matérn covariance function can be expressed as a product | What is the rationale of the Matérn covariance function?
I do not know, but I found this question very interesting and here's what I got after a bit of reading on it.
For certain values of $\nu$, the Matérn covariance function can be expressed as a product of an exponential and a polynomial. E.g. for $\nu = 5/2$:
$$C_{... | What is the rationale of the Matérn covariance function?
I do not know, but I found this question very interesting and here's what I got after a bit of reading on it.
For certain values of $\nu$, the Matérn covariance function can be expressed as a product |
5,542 | What is the rationale of the Matérn covariance function? | There is one aspect of Matérn covariance functions that makes them very useful for physical systems:
It describes an electrical signal with white Gaussian noise passing through an RC low-pass filter. The output signal is time-correlated according to the Matérn covariance function $\nu= 1/2$. When this output signal pas... | What is the rationale of the Matérn covariance function? | There is one aspect of Matérn covariance functions that makes them very useful for physical systems:
It describes an electrical signal with white Gaussian noise passing through an RC low-pass filter. | What is the rationale of the Matérn covariance function?
There is one aspect of Matérn covariance functions that makes them very useful for physical systems:
It describes an electrical signal with white Gaussian noise passing through an RC low-pass filter. The output signal is time-correlated according to the Matérn co... | What is the rationale of the Matérn covariance function?
There is one aspect of Matérn covariance functions that makes them very useful for physical systems:
It describes an electrical signal with white Gaussian noise passing through an RC low-pass filter. |
5,543 | What is the rationale of the Matérn covariance function? | Adding to the excellent comments already made on this great question, I'd like to highlight the fact that the power spectrum of the 1-dimensional Matérn covariance function is a non-standardized Student's t-distribution, offering another potential viewpoint for interpretation. | What is the rationale of the Matérn covariance function? | Adding to the excellent comments already made on this great question, I'd like to highlight the fact that the power spectrum of the 1-dimensional Matérn covariance function is a non-standardized Stude | What is the rationale of the Matérn covariance function?
Adding to the excellent comments already made on this great question, I'd like to highlight the fact that the power spectrum of the 1-dimensional Matérn covariance function is a non-standardized Student's t-distribution, offering another potential viewpoint for i... | What is the rationale of the Matérn covariance function?
Adding to the excellent comments already made on this great question, I'd like to highlight the fact that the power spectrum of the 1-dimensional Matérn covariance function is a non-standardized Stude |
5,544 | Gamma vs. lognormal distributions | As for qualitative differences, the lognormal and gamma are, as you say, quite similar.
Indeed, in practice they're often used to model the same phenomena (some people will use a gamma where others use a lognormal). They are both, for example, constant-coefficient-of-variation models (the CV for the lognormal is $\sqrt... | Gamma vs. lognormal distributions | As for qualitative differences, the lognormal and gamma are, as you say, quite similar.
Indeed, in practice they're often used to model the same phenomena (some people will use a gamma where others us | Gamma vs. lognormal distributions
As for qualitative differences, the lognormal and gamma are, as you say, quite similar.
Indeed, in practice they're often used to model the same phenomena (some people will use a gamma where others use a lognormal). They are both, for example, constant-coefficient-of-variation models (... | Gamma vs. lognormal distributions
As for qualitative differences, the lognormal and gamma are, as you say, quite similar.
Indeed, in practice they're often used to model the same phenomena (some people will use a gamma where others us |
5,545 | Gamma vs. lognormal distributions | Yes, the gamma distribution is the maximum entropy distribution for which the mean $E(X)$ and mean-log $E(\log X)$ are fixed. As with all exponential family distributions, it is the unique maximum entropy distribution for a fixed expected sufficient statistic.
To answer your question about physical processes that gene... | Gamma vs. lognormal distributions | Yes, the gamma distribution is the maximum entropy distribution for which the mean $E(X)$ and mean-log $E(\log X)$ are fixed. As with all exponential family distributions, it is the unique maximum en | Gamma vs. lognormal distributions
Yes, the gamma distribution is the maximum entropy distribution for which the mean $E(X)$ and mean-log $E(\log X)$ are fixed. As with all exponential family distributions, it is the unique maximum entropy distribution for a fixed expected sufficient statistic.
To answer your question ... | Gamma vs. lognormal distributions
Yes, the gamma distribution is the maximum entropy distribution for which the mean $E(X)$ and mean-log $E(\log X)$ are fixed. As with all exponential family distributions, it is the unique maximum en |
5,546 | Rigorous definition of an outlier? | As long as your data comes from a known distribution with known properties, you can rigorously define an outlier as an event that is too unlikely to have been generated by the observed process (if you consider "too unlikely" to be non-rigorous, then all hypothesis testing is).
However, this approach is problematic on t... | Rigorous definition of an outlier? | As long as your data comes from a known distribution with known properties, you can rigorously define an outlier as an event that is too unlikely to have been generated by the observed process (if you | Rigorous definition of an outlier?
As long as your data comes from a known distribution with known properties, you can rigorously define an outlier as an event that is too unlikely to have been generated by the observed process (if you consider "too unlikely" to be non-rigorous, then all hypothesis testing is).
However... | Rigorous definition of an outlier?
As long as your data comes from a known distribution with known properties, you can rigorously define an outlier as an event that is too unlikely to have been generated by the observed process (if you |
5,547 | Rigorous definition of an outlier? | You are correct that removing outliers can look like a subjective exercise but that doesn't mean that it's wrong. The compulsive need to always have a rigorous mathematical reason for every decision regarding your data analysis is often just a thin veil of artificial rigour over what turns out to be a subjective exerc... | Rigorous definition of an outlier? | You are correct that removing outliers can look like a subjective exercise but that doesn't mean that it's wrong. The compulsive need to always have a rigorous mathematical reason for every decision | Rigorous definition of an outlier?
You are correct that removing outliers can look like a subjective exercise but that doesn't mean that it's wrong. The compulsive need to always have a rigorous mathematical reason for every decision regarding your data analysis is often just a thin veil of artificial rigour over what... | Rigorous definition of an outlier?
You are correct that removing outliers can look like a subjective exercise but that doesn't mean that it's wrong. The compulsive need to always have a rigorous mathematical reason for every decision |
5,548 | Rigorous definition of an outlier? | I don't think it is possible to define an outlier without assuming a model of the underlying process giving rise to the data. Without such a model we have no frame of reference to decide whether the data are anomalous or "wrong". The definition of an outlier that I have found useful is that an outlier is an observati... | Rigorous definition of an outlier? | I don't think it is possible to define an outlier without assuming a model of the underlying process giving rise to the data. Without such a model we have no frame of reference to decide whether the | Rigorous definition of an outlier?
I don't think it is possible to define an outlier without assuming a model of the underlying process giving rise to the data. Without such a model we have no frame of reference to decide whether the data are anomalous or "wrong". The definition of an outlier that I have found useful... | Rigorous definition of an outlier?
I don't think it is possible to define an outlier without assuming a model of the underlying process giving rise to the data. Without such a model we have no frame of reference to decide whether the |
5,549 | Rigorous definition of an outlier? | There are many excellent answers here. However, I want to point out that two questions are being confused. The first is, 'what is an outlier?', and more specifically to give a "rigorous definition" of such. This is simple:
An outlier is a data point that comes from a different population /
distribution / data g... | Rigorous definition of an outlier? | There are many excellent answers here. However, I want to point out that two questions are being confused. The first is, 'what is an outlier?', and more specifically to give a "rigorous definition" | Rigorous definition of an outlier?
There are many excellent answers here. However, I want to point out that two questions are being confused. The first is, 'what is an outlier?', and more specifically to give a "rigorous definition" of such. This is simple:
An outlier is a data point that comes from a different p... | Rigorous definition of an outlier?
There are many excellent answers here. However, I want to point out that two questions are being confused. The first is, 'what is an outlier?', and more specifically to give a "rigorous definition" |
5,550 | Rigorous definition of an outlier? | Definition 1: As already mentioned, an outlier in a group of data reflecting the same process (say process A) is an observation (or a set of observations) that is unlikely to be a result of process A.
This definition certainly involves an estimation of the likelihood function of the process A (hence a model) and sett... | Rigorous definition of an outlier? | Definition 1: As already mentioned, an outlier in a group of data reflecting the same process (say process A) is an observation (or a set of observations) that is unlikely to be a result of process A | Rigorous definition of an outlier?
Definition 1: As already mentioned, an outlier in a group of data reflecting the same process (say process A) is an observation (or a set of observations) that is unlikely to be a result of process A.
This definition certainly involves an estimation of the likelihood function of the... | Rigorous definition of an outlier?
Definition 1: As already mentioned, an outlier in a group of data reflecting the same process (say process A) is an observation (or a set of observations) that is unlikely to be a result of process A |
5,551 | Rigorous definition of an outlier? | An outlier is a data point that is inconvenient to me, given my current understanding of the process that generates this data.
I believe this definition is as rigorous as can be made. | Rigorous definition of an outlier? | An outlier is a data point that is inconvenient to me, given my current understanding of the process that generates this data.
I believe this definition is as rigorous as can be made. | Rigorous definition of an outlier?
An outlier is a data point that is inconvenient to me, given my current understanding of the process that generates this data.
I believe this definition is as rigorous as can be made. | Rigorous definition of an outlier?
An outlier is a data point that is inconvenient to me, given my current understanding of the process that generates this data.
I believe this definition is as rigorous as can be made. |
5,552 | Rigorous definition of an outlier? | define an outlier as a member of that minimal set of elements which must be removed from a datasetof size n in order to assure 100% compliance with RUM tests conducted at 95% confidence level on all (2^n -1) unique subsets of the data. See Karian and Dudewicz text on fitting data to pdfs using R(Sept 2010) for defin... | Rigorous definition of an outlier? | define an outlier as a member of that minimal set of elements which must be removed from a datasetof size n in order to assure 100% compliance with RUM tests conducted at 95% confidence level on all | Rigorous definition of an outlier?
define an outlier as a member of that minimal set of elements which must be removed from a datasetof size n in order to assure 100% compliance with RUM tests conducted at 95% confidence level on all (2^n -1) unique subsets of the data. See Karian and Dudewicz text on fitting data to... | Rigorous definition of an outlier?
define an outlier as a member of that minimal set of elements which must be removed from a datasetof size n in order to assure 100% compliance with RUM tests conducted at 95% confidence level on all |
5,553 | Rigorous definition of an outlier? | Outliers are important only in the frequentist realm. If a single datapoint adds bias to your model which is defined by an underlying distribution predeterimined by your theory, then it is an outlier for that model. The subjectivity lies in the fact that if your theory posits a different model, then you can have a diff... | Rigorous definition of an outlier? | Outliers are important only in the frequentist realm. If a single datapoint adds bias to your model which is defined by an underlying distribution predeterimined by your theory, then it is an outlier | Rigorous definition of an outlier?
Outliers are important only in the frequentist realm. If a single datapoint adds bias to your model which is defined by an underlying distribution predeterimined by your theory, then it is an outlier for that model. The subjectivity lies in the fact that if your theory posits a differ... | Rigorous definition of an outlier?
Outliers are important only in the frequentist realm. If a single datapoint adds bias to your model which is defined by an underlying distribution predeterimined by your theory, then it is an outlier |
5,554 | Statistical models cheat sheet | I have previously found UCLA's "Choosing the Correct Statistical Test" to be helpful:
https://stats.idre.ucla.edu/other/mult-pkg/whatstat/
It also gives examples of how to do the analysis in SAS, Stata, SPSS and R. | Statistical models cheat sheet | I have previously found UCLA's "Choosing the Correct Statistical Test" to be helpful:
https://stats.idre.ucla.edu/other/mult-pkg/whatstat/
It also gives examples of how to do the analysis in SAS, Stat | Statistical models cheat sheet
I have previously found UCLA's "Choosing the Correct Statistical Test" to be helpful:
https://stats.idre.ucla.edu/other/mult-pkg/whatstat/
It also gives examples of how to do the analysis in SAS, Stata, SPSS and R. | Statistical models cheat sheet
I have previously found UCLA's "Choosing the Correct Statistical Test" to be helpful:
https://stats.idre.ucla.edu/other/mult-pkg/whatstat/
It also gives examples of how to do the analysis in SAS, Stat |
5,555 | Statistical models cheat sheet | Do you mean a statistical analysis decision tree? (google search), like this (only with extensions):
(source: processma.com)
?
BTW, notice that the chart in wrong in that the tests it offers for median are not for median but for rank... (it would be for median if the distribution is symmetrical) | Statistical models cheat sheet | Do you mean a statistical analysis decision tree? (google search), like this (only with extensions):
(source: processma.com)
?
BTW, notice that the chart in wrong in that the tests it offers for med | Statistical models cheat sheet
Do you mean a statistical analysis decision tree? (google search), like this (only with extensions):
(source: processma.com)
?
BTW, notice that the chart in wrong in that the tests it offers for median are not for median but for rank... (it would be for median if the distribution is sym... | Statistical models cheat sheet
Do you mean a statistical analysis decision tree? (google search), like this (only with extensions):
(source: processma.com)
?
BTW, notice that the chart in wrong in that the tests it offers for med |
5,556 | Statistical models cheat sheet | Reading "Using Multivariate Statistics (4th Edition) Barbara G. Tabachnick"
I found these decision trees based on major research question. I think they are quite useful. Following this link you'll find an extract of the book
http://www.psychwiki.com/images/d/d8/TF2.pdf
see pages 29 to 31 | Statistical models cheat sheet | Reading "Using Multivariate Statistics (4th Edition) Barbara G. Tabachnick"
I found these decision trees based on major research question. I think they are quite useful. Following this link you'll fi | Statistical models cheat sheet
Reading "Using Multivariate Statistics (4th Edition) Barbara G. Tabachnick"
I found these decision trees based on major research question. I think they are quite useful. Following this link you'll find an extract of the book
http://www.psychwiki.com/images/d/d8/TF2.pdf
see pages 29 to 31 | Statistical models cheat sheet
Reading "Using Multivariate Statistics (4th Edition) Barbara G. Tabachnick"
I found these decision trees based on major research question. I think they are quite useful. Following this link you'll fi |
5,557 | Statistical models cheat sheet | Here is a collection page:
http://sasdataguru.blogspot.com/2011/05/online-statistics-cheat-sheet.html | Statistical models cheat sheet | Here is a collection page:
http://sasdataguru.blogspot.com/2011/05/online-statistics-cheat-sheet.html | Statistical models cheat sheet
Here is a collection page:
http://sasdataguru.blogspot.com/2011/05/online-statistics-cheat-sheet.html | Statistical models cheat sheet
Here is a collection page:
http://sasdataguru.blogspot.com/2011/05/online-statistics-cheat-sheet.html |
5,558 | Statistical models cheat sheet | Since when is regression an hypothesis test of anything? If by"regression"why is meant is curve fitting or correlations (pair-wise or multiple) the only "test" is between some relation vs. no relation. Figures like this own their origin to Siege's l956 book. | Statistical models cheat sheet | Since when is regression an hypothesis test of anything? If by"regression"why is meant is curve fitting or correlations (pair-wise or multiple) the only "test" is between some relation vs. no relatio | Statistical models cheat sheet
Since when is regression an hypothesis test of anything? If by"regression"why is meant is curve fitting or correlations (pair-wise or multiple) the only "test" is between some relation vs. no relation. Figures like this own their origin to Siege's l956 book. | Statistical models cheat sheet
Since when is regression an hypothesis test of anything? If by"regression"why is meant is curve fitting or correlations (pair-wise or multiple) the only "test" is between some relation vs. no relatio |
5,559 | Optimized implementations of the Random Forest algorithm | (Updated 6 IX 2015 with suggestions from comments, also made CW)
There are two new, nice packages available for R which are pretty well optimised for a certain conditions:
ranger -- C++, R package, optimised for $p>>n$ problems, parallel, special treatment of GWAS data.
Arborist -- C++, R and Python bindings, optimise... | Optimized implementations of the Random Forest algorithm | (Updated 6 IX 2015 with suggestions from comments, also made CW)
There are two new, nice packages available for R which are pretty well optimised for a certain conditions:
ranger -- C++, R package, o | Optimized implementations of the Random Forest algorithm
(Updated 6 IX 2015 with suggestions from comments, also made CW)
There are two new, nice packages available for R which are pretty well optimised for a certain conditions:
ranger -- C++, R package, optimised for $p>>n$ problems, parallel, special treatment of GW... | Optimized implementations of the Random Forest algorithm
(Updated 6 IX 2015 with suggestions from comments, also made CW)
There are two new, nice packages available for R which are pretty well optimised for a certain conditions:
ranger -- C++, R package, o |
5,560 | Optimized implementations of the Random Forest algorithm | As far as I know, the R version of randomForest calls the same Fortran code as the original version. Furthermore, it's trivial to parallelize the randomForest function. It's actually one of the examples provided in the foreach documentation.
library(foreach)
library(randomForest)
rf <- foreach(ntree = rep(250, 4), .co... | Optimized implementations of the Random Forest algorithm | As far as I know, the R version of randomForest calls the same Fortran code as the original version. Furthermore, it's trivial to parallelize the randomForest function. It's actually one of the examp | Optimized implementations of the Random Forest algorithm
As far as I know, the R version of randomForest calls the same Fortran code as the original version. Furthermore, it's trivial to parallelize the randomForest function. It's actually one of the examples provided in the foreach documentation.
library(foreach)
lib... | Optimized implementations of the Random Forest algorithm
As far as I know, the R version of randomForest calls the same Fortran code as the original version. Furthermore, it's trivial to parallelize the randomForest function. It's actually one of the examp |
5,561 | Optimized implementations of the Random Forest algorithm | The ELSII used randomForest (see e.g., footnote 3 p.591), which is an R implementation of the Breiman and Cutler's Fortran code from Salford. Andy Liaw's code is in C.
There's another implementation of RFs proposed in the party package (in C), which relies on R/Lapack, which has some dependencies on BLAS (see/include/R... | Optimized implementations of the Random Forest algorithm | The ELSII used randomForest (see e.g., footnote 3 p.591), which is an R implementation of the Breiman and Cutler's Fortran code from Salford. Andy Liaw's code is in C.
There's another implementation o | Optimized implementations of the Random Forest algorithm
The ELSII used randomForest (see e.g., footnote 3 p.591), which is an R implementation of the Breiman and Cutler's Fortran code from Salford. Andy Liaw's code is in C.
There's another implementation of RFs proposed in the party package (in C), which relies on R/L... | Optimized implementations of the Random Forest algorithm
The ELSII used randomForest (see e.g., footnote 3 p.591), which is an R implementation of the Breiman and Cutler's Fortran code from Salford. Andy Liaw's code is in C.
There's another implementation o |
5,562 | Optimized implementations of the Random Forest algorithm | The team behind randomJungle claims that is an order of magnitude faster than
the R randomForest implementation and uses an order magnitude less memory.
A package for randomJungle is being developed for R but I can't get to build yet.
https://r-forge.r-project.org/projects/rjungler/ | Optimized implementations of the Random Forest algorithm | The team behind randomJungle claims that is an order of magnitude faster than
the R randomForest implementation and uses an order magnitude less memory.
A package for randomJungle is being developed | Optimized implementations of the Random Forest algorithm
The team behind randomJungle claims that is an order of magnitude faster than
the R randomForest implementation and uses an order magnitude less memory.
A package for randomJungle is being developed for R but I can't get to build yet.
https://r-forge.r-project.o... | Optimized implementations of the Random Forest algorithm
The team behind randomJungle claims that is an order of magnitude faster than
the R randomForest implementation and uses an order magnitude less memory.
A package for randomJungle is being developed |
5,563 | Optimized implementations of the Random Forest algorithm | For the Javascript Implementation go through this demo.
If you are like a child who is hungry for a chocolate, here is your chocolate of random forest
http://cs.stanford.edu/people/karpathy/svmjs/demo/demoforest.html | Optimized implementations of the Random Forest algorithm | For the Javascript Implementation go through this demo.
If you are like a child who is hungry for a chocolate, here is your chocolate of random forest
http://cs.stanford.edu/people/karpathy/svmjs/de | Optimized implementations of the Random Forest algorithm
For the Javascript Implementation go through this demo.
If you are like a child who is hungry for a chocolate, here is your chocolate of random forest
http://cs.stanford.edu/people/karpathy/svmjs/demo/demoforest.html | Optimized implementations of the Random Forest algorithm
For the Javascript Implementation go through this demo.
If you are like a child who is hungry for a chocolate, here is your chocolate of random forest
http://cs.stanford.edu/people/karpathy/svmjs/de |
5,564 | whether to rescale indicator / binary / dummy predictors for LASSO | According Tibshirani (THE LASSO METHOD FOR VARIABLE SELECTION
IN THE COX MODEL, Statistics in Medicine, VOL. 16, 385-395 (1997)), who literally wrote the book on regularization methods, you should standardize the dummies. However, you then lose the straightforward interpretability of your coefficients. If you don't, ... | whether to rescale indicator / binary / dummy predictors for LASSO | According Tibshirani (THE LASSO METHOD FOR VARIABLE SELECTION
IN THE COX MODEL, Statistics in Medicine, VOL. 16, 385-395 (1997)), who literally wrote the book on regularization methods, you should sta | whether to rescale indicator / binary / dummy predictors for LASSO
According Tibshirani (THE LASSO METHOD FOR VARIABLE SELECTION
IN THE COX MODEL, Statistics in Medicine, VOL. 16, 385-395 (1997)), who literally wrote the book on regularization methods, you should standardize the dummies. However, you then lose the str... | whether to rescale indicator / binary / dummy predictors for LASSO
According Tibshirani (THE LASSO METHOD FOR VARIABLE SELECTION
IN THE COX MODEL, Statistics in Medicine, VOL. 16, 385-395 (1997)), who literally wrote the book on regularization methods, you should sta |
5,565 | whether to rescale indicator / binary / dummy predictors for LASSO | Andrew Gelman's blog post, When to standardize regression inputs and when to leave them alone, is also worth a look. This part in particular is relevant:
For comparing coefficients for different predictors within a model, standardizing gets the nod. (Although I don’t standardize binary inputs. I code them as 0/1, and... | whether to rescale indicator / binary / dummy predictors for LASSO | Andrew Gelman's blog post, When to standardize regression inputs and when to leave them alone, is also worth a look. This part in particular is relevant:
For comparing coefficients for different pre | whether to rescale indicator / binary / dummy predictors for LASSO
Andrew Gelman's blog post, When to standardize regression inputs and when to leave them alone, is also worth a look. This part in particular is relevant:
For comparing coefficients for different predictors within a model, standardizing gets the nod. (... | whether to rescale indicator / binary / dummy predictors for LASSO
Andrew Gelman's blog post, When to standardize regression inputs and when to leave them alone, is also worth a look. This part in particular is relevant:
For comparing coefficients for different pre |
5,566 | whether to rescale indicator / binary / dummy predictors for LASSO | This is more of a comment, but too long. One of the most used softwares for lasso (and friends) is R's glmnet. From the help page, printed by ?glmnet:
standardize: Logical flag for x variable standardization, prior to
fitting the model sequence. The coefficients are always
returned on the ori... | whether to rescale indicator / binary / dummy predictors for LASSO | This is more of a comment, but too long. One of the most used softwares for lasso (and friends) is R's glmnet. From the help page, printed by ?glmnet:
standardize: Logical flag for x variable stand | whether to rescale indicator / binary / dummy predictors for LASSO
This is more of a comment, but too long. One of the most used softwares for lasso (and friends) is R's glmnet. From the help page, printed by ?glmnet:
standardize: Logical flag for x variable standardization, prior to
fitting the model se... | whether to rescale indicator / binary / dummy predictors for LASSO
This is more of a comment, but too long. One of the most used softwares for lasso (and friends) is R's glmnet. From the help page, printed by ?glmnet:
standardize: Logical flag for x variable stand |
5,567 | How to do community detection in a weighted social network/graph? | igraph implementation of Newman's modularity clustering (fastgreedy function) can be used with weighted edges as well. Just add weight attribute to the edges and analyse as usual. In my experience, it run even faster with weights as there are less ties. | How to do community detection in a weighted social network/graph? | igraph implementation of Newman's modularity clustering (fastgreedy function) can be used with weighted edges as well. Just add weight attribute to the edges and analyse as usual. In my experience, i | How to do community detection in a weighted social network/graph?
igraph implementation of Newman's modularity clustering (fastgreedy function) can be used with weighted edges as well. Just add weight attribute to the edges and analyse as usual. In my experience, it run even faster with weights as there are less ties. | How to do community detection in a weighted social network/graph?
igraph implementation of Newman's modularity clustering (fastgreedy function) can be used with weighted edges as well. Just add weight attribute to the edges and analyse as usual. In my experience, i |
5,568 | How to do community detection in a weighted social network/graph? | I know that Gephi can process undirected weighted graph, but I seem to remember it has to be stored in GDF, which is pretty close to CSV, or Ucinet DL. Be aware that it's still an alpha release.
Now, about clustering your graph, Gephi seems to lack clustering pipelines, except for the MCL algorithm that is now availabl... | How to do community detection in a weighted social network/graph? | I know that Gephi can process undirected weighted graph, but I seem to remember it has to be stored in GDF, which is pretty close to CSV, or Ucinet DL. Be aware that it's still an alpha release.
Now, | How to do community detection in a weighted social network/graph?
I know that Gephi can process undirected weighted graph, but I seem to remember it has to be stored in GDF, which is pretty close to CSV, or Ucinet DL. Be aware that it's still an alpha release.
Now, about clustering your graph, Gephi seems to lack clust... | How to do community detection in a weighted social network/graph?
I know that Gephi can process undirected weighted graph, but I seem to remember it has to be stored in GDF, which is pretty close to CSV, or Ucinet DL. Be aware that it's still an alpha release.
Now, |
5,569 | How to do community detection in a weighted social network/graph? | Gephi implements the Louvain Modularity method: http://wiki.gephi.org/index.php/Modularity
cheers | How to do community detection in a weighted social network/graph? | Gephi implements the Louvain Modularity method: http://wiki.gephi.org/index.php/Modularity
cheers | How to do community detection in a weighted social network/graph?
Gephi implements the Louvain Modularity method: http://wiki.gephi.org/index.php/Modularity
cheers | How to do community detection in a weighted social network/graph?
Gephi implements the Louvain Modularity method: http://wiki.gephi.org/index.php/Modularity
cheers |
5,570 | How to do community detection in a weighted social network/graph? | The Louvain modularity algorithm is available in C++:
https://sites.google.com/site/findcommunities/
It deals with weighted networks of millions of nodes and edges, and has been demonstrated to be much faster than Newman algorithm. | How to do community detection in a weighted social network/graph? | The Louvain modularity algorithm is available in C++:
https://sites.google.com/site/findcommunities/
It deals with weighted networks of millions of nodes and edges, and has been demonstrated to be muc | How to do community detection in a weighted social network/graph?
The Louvain modularity algorithm is available in C++:
https://sites.google.com/site/findcommunities/
It deals with weighted networks of millions of nodes and edges, and has been demonstrated to be much faster than Newman algorithm. | How to do community detection in a weighted social network/graph?
The Louvain modularity algorithm is available in C++:
https://sites.google.com/site/findcommunities/
It deals with weighted networks of millions of nodes and edges, and has been demonstrated to be muc |
5,571 | How to do community detection in a weighted social network/graph? | If you are using python, and have created a weighted graph using NetworkX, then you can use python-louvain for clustering. Where G is a weighted graph:
import community
partition = community.best_partition(G, weight='weight') | How to do community detection in a weighted social network/graph? | If you are using python, and have created a weighted graph using NetworkX, then you can use python-louvain for clustering. Where G is a weighted graph:
import community
partition = community.best_par | How to do community detection in a weighted social network/graph?
If you are using python, and have created a weighted graph using NetworkX, then you can use python-louvain for clustering. Where G is a weighted graph:
import community
partition = community.best_partition(G, weight='weight') | How to do community detection in a weighted social network/graph?
If you are using python, and have created a weighted graph using NetworkX, then you can use python-louvain for clustering. Where G is a weighted graph:
import community
partition = community.best_par |
5,572 | How to do community detection in a weighted social network/graph? | I just came across the tnet package for R. The creator seems to be researching on community discovery in weighted and bipartite (two-mode) graphs.
http://opsahl.co.uk/tnet/content/view/15/27/
I have not yet use it. | How to do community detection in a weighted social network/graph? | I just came across the tnet package for R. The creator seems to be researching on community discovery in weighted and bipartite (two-mode) graphs.
http://opsahl.co.uk/tnet/content/view/15/27/
I have n | How to do community detection in a weighted social network/graph?
I just came across the tnet package for R. The creator seems to be researching on community discovery in weighted and bipartite (two-mode) graphs.
http://opsahl.co.uk/tnet/content/view/15/27/
I have not yet use it. | How to do community detection in a weighted social network/graph?
I just came across the tnet package for R. The creator seems to be researching on community discovery in weighted and bipartite (two-mode) graphs.
http://opsahl.co.uk/tnet/content/view/15/27/
I have n |
5,573 | How to do community detection in a weighted social network/graph? | SLPA (now called GANXiS) is a fast algorithm capable of detecting both disjoint and overlapping communities in social networks (undirected/directed and unweighted/weighted). It is shown that the algorithm produces meaningful results on real-world social and gene networks. It is one of the state-of-the-art. It is ava... | How to do community detection in a weighted social network/graph? | SLPA (now called GANXiS) is a fast algorithm capable of detecting both disjoint and overlapping communities in social networks (undirected/directed and unweighted/weighted). It is shown that the al | How to do community detection in a weighted social network/graph?
SLPA (now called GANXiS) is a fast algorithm capable of detecting both disjoint and overlapping communities in social networks (undirected/directed and unweighted/weighted). It is shown that the algorithm produces meaningful results on real-world soci... | How to do community detection in a weighted social network/graph?
SLPA (now called GANXiS) is a fast algorithm capable of detecting both disjoint and overlapping communities in social networks (undirected/directed and unweighted/weighted). It is shown that the al |
5,574 | How to do community detection in a weighted social network/graph? | I've an java implementation for non-overlapping, weighted/unweighted network that could probably handle 3 million nodes (I've tested it for a million node dataset). However, it works like k-means, and needs the number of partitions to be detected as an input (k in kmeans). You can find more info here, and here is the c... | How to do community detection in a weighted social network/graph? | I've an java implementation for non-overlapping, weighted/unweighted network that could probably handle 3 million nodes (I've tested it for a million node dataset). However, it works like k-means, and | How to do community detection in a weighted social network/graph?
I've an java implementation for non-overlapping, weighted/unweighted network that could probably handle 3 million nodes (I've tested it for a million node dataset). However, it works like k-means, and needs the number of partitions to be detected as an i... | How to do community detection in a weighted social network/graph?
I've an java implementation for non-overlapping, weighted/unweighted network that could probably handle 3 million nodes (I've tested it for a million node dataset). However, it works like k-means, and |
5,575 | Why does Andrew Ng prefer to use SVD and not EIG of covariance matrix to do PCA? | amoeba already gave a good answer in the comments, but if you want a formal argument, here it goes.
The singular value decomposition of a matrix $A$ is $A=U\Sigma V^T$, where the columns of $V$ are eigenvectors of $A^TA$ and the diagonal entries of $\Sigma$ are the square roots of its eigenvalues, i.e. $\sigma_{ii}=\sq... | Why does Andrew Ng prefer to use SVD and not EIG of covariance matrix to do PCA? | amoeba already gave a good answer in the comments, but if you want a formal argument, here it goes.
The singular value decomposition of a matrix $A$ is $A=U\Sigma V^T$, where the columns of $V$ are ei | Why does Andrew Ng prefer to use SVD and not EIG of covariance matrix to do PCA?
amoeba already gave a good answer in the comments, but if you want a formal argument, here it goes.
The singular value decomposition of a matrix $A$ is $A=U\Sigma V^T$, where the columns of $V$ are eigenvectors of $A^TA$ and the diagonal e... | Why does Andrew Ng prefer to use SVD and not EIG of covariance matrix to do PCA?
amoeba already gave a good answer in the comments, but if you want a formal argument, here it goes.
The singular value decomposition of a matrix $A$ is $A=U\Sigma V^T$, where the columns of $V$ are ei |
5,576 | Why does Andrew Ng prefer to use SVD and not EIG of covariance matrix to do PCA? | @amoeba had excellent answers to PCA questions, including this one on relation of SVD to PCA. Answering to your exact question I'll make three points:
mathematically there is no difference whether you calculate PCA on the data matrix directly or on its covariance matrix
the difference is purely due to numerical precis... | Why does Andrew Ng prefer to use SVD and not EIG of covariance matrix to do PCA? | @amoeba had excellent answers to PCA questions, including this one on relation of SVD to PCA. Answering to your exact question I'll make three points:
mathematically there is no difference whether yo | Why does Andrew Ng prefer to use SVD and not EIG of covariance matrix to do PCA?
@amoeba had excellent answers to PCA questions, including this one on relation of SVD to PCA. Answering to your exact question I'll make three points:
mathematically there is no difference whether you calculate PCA on the data matrix dire... | Why does Andrew Ng prefer to use SVD and not EIG of covariance matrix to do PCA?
@amoeba had excellent answers to PCA questions, including this one on relation of SVD to PCA. Answering to your exact question I'll make three points:
mathematically there is no difference whether yo |
5,577 | Why does Andrew Ng prefer to use SVD and not EIG of covariance matrix to do PCA? | For Python users, I'd like to point out that for symmetric matrices (like the covariance matrix), it is better to use numpy.linalg.eigh function instead of a general numpy.linalg.eig function.
eigh is 9-10 times faster than eig on my computer (regardless of matrix size) and has better accuracy (based on @Aksakal's accu... | Why does Andrew Ng prefer to use SVD and not EIG of covariance matrix to do PCA? | For Python users, I'd like to point out that for symmetric matrices (like the covariance matrix), it is better to use numpy.linalg.eigh function instead of a general numpy.linalg.eig function.
eigh is | Why does Andrew Ng prefer to use SVD and not EIG of covariance matrix to do PCA?
For Python users, I'd like to point out that for symmetric matrices (like the covariance matrix), it is better to use numpy.linalg.eigh function instead of a general numpy.linalg.eig function.
eigh is 9-10 times faster than eig on my compu... | Why does Andrew Ng prefer to use SVD and not EIG of covariance matrix to do PCA?
For Python users, I'd like to point out that for symmetric matrices (like the covariance matrix), it is better to use numpy.linalg.eigh function instead of a general numpy.linalg.eig function.
eigh is |
5,578 | Why does Andrew Ng prefer to use SVD and not EIG of covariance matrix to do PCA? | Some great answers already have been given to your questions, so I won't add a lot of new stuff. But I tried (i) to base my answer on the knowledge you seem to have and (ii) to be as concise as possible. So you - or others in a similar situation - may find this answer helpful.
(Simple) Mathematical Explanation
SVD and ... | Why does Andrew Ng prefer to use SVD and not EIG of covariance matrix to do PCA? | Some great answers already have been given to your questions, so I won't add a lot of new stuff. But I tried (i) to base my answer on the knowledge you seem to have and (ii) to be as concise as possib | Why does Andrew Ng prefer to use SVD and not EIG of covariance matrix to do PCA?
Some great answers already have been given to your questions, so I won't add a lot of new stuff. But I tried (i) to base my answer on the knowledge you seem to have and (ii) to be as concise as possible. So you - or others in a similar sit... | Why does Andrew Ng prefer to use SVD and not EIG of covariance matrix to do PCA?
Some great answers already have been given to your questions, so I won't add a lot of new stuff. But I tried (i) to base my answer on the knowledge you seem to have and (ii) to be as concise as possib |
5,579 | Why does Andrew Ng prefer to use SVD and not EIG of covariance matrix to do PCA? | To answer the last part of your question, "Why do they do SVD of covariance matrix, not data matrix?" I believe it is for performance and storage reasons. Typically, $m$ will be a very large number and even if $n$ is large, we would expect $m \gg n$.
Calculating the covariance matrix and then performing SVD on that is ... | Why does Andrew Ng prefer to use SVD and not EIG of covariance matrix to do PCA? | To answer the last part of your question, "Why do they do SVD of covariance matrix, not data matrix?" I believe it is for performance and storage reasons. Typically, $m$ will be a very large number an | Why does Andrew Ng prefer to use SVD and not EIG of covariance matrix to do PCA?
To answer the last part of your question, "Why do they do SVD of covariance matrix, not data matrix?" I believe it is for performance and storage reasons. Typically, $m$ will be a very large number and even if $n$ is large, we would expect... | Why does Andrew Ng prefer to use SVD and not EIG of covariance matrix to do PCA?
To answer the last part of your question, "Why do they do SVD of covariance matrix, not data matrix?" I believe it is for performance and storage reasons. Typically, $m$ will be a very large number an |
5,580 | Why does Andrew Ng prefer to use SVD and not EIG of covariance matrix to do PCA? | If you apply SVD on the covariance matrix, your principal vectors are the same as applying SVD on the data matrix. So, mathematically they are equivalent in this case.
However, in terms of complexity, it does not make much sense to apply SVD on the covariance matrix: you have constructed the covariance matrix and then ... | Why does Andrew Ng prefer to use SVD and not EIG of covariance matrix to do PCA? | If you apply SVD on the covariance matrix, your principal vectors are the same as applying SVD on the data matrix. So, mathematically they are equivalent in this case.
However, in terms of complexity, | Why does Andrew Ng prefer to use SVD and not EIG of covariance matrix to do PCA?
If you apply SVD on the covariance matrix, your principal vectors are the same as applying SVD on the data matrix. So, mathematically they are equivalent in this case.
However, in terms of complexity, it does not make much sense to apply S... | Why does Andrew Ng prefer to use SVD and not EIG of covariance matrix to do PCA?
If you apply SVD on the covariance matrix, your principal vectors are the same as applying SVD on the data matrix. So, mathematically they are equivalent in this case.
However, in terms of complexity, |
5,581 | Why does Andrew Ng prefer to use SVD and not EIG of covariance matrix to do PCA? | If anyone cares about performance difference in a specific case, I compared
SVD and Eigen-analysys on a 632x632 real symmetric matrix L using C++/Eigen.
I used BDCSVD
// compute full V, U *not* needed
Eigen::BDCSVD<Eigen::MatrixXf> svd(L,Eigen::ComputeFullV);
and SelfAdjointEigenSolver
Eigen::SelfAdjointEigenSolver<Ei... | Why does Andrew Ng prefer to use SVD and not EIG of covariance matrix to do PCA? | If anyone cares about performance difference in a specific case, I compared
SVD and Eigen-analysys on a 632x632 real symmetric matrix L using C++/Eigen.
I used BDCSVD
// compute full V, U *not* needed | Why does Andrew Ng prefer to use SVD and not EIG of covariance matrix to do PCA?
If anyone cares about performance difference in a specific case, I compared
SVD and Eigen-analysys on a 632x632 real symmetric matrix L using C++/Eigen.
I used BDCSVD
// compute full V, U *not* needed
Eigen::BDCSVD<Eigen::MatrixXf> svd(L,E... | Why does Andrew Ng prefer to use SVD and not EIG of covariance matrix to do PCA?
If anyone cares about performance difference in a specific case, I compared
SVD and Eigen-analysys on a 632x632 real symmetric matrix L using C++/Eigen.
I used BDCSVD
// compute full V, U *not* needed |
5,582 | Neural Networks: weight change momentum and weight decay | Yes, it's very common to use both tricks. They solve different problems and can work well together.
One way to think about it is that weight decay changes the function that's being optimized, while momentum changes the path you take to the optimum.
Weight decay, by shrinking your coefficients toward zero, ensures that... | Neural Networks: weight change momentum and weight decay | Yes, it's very common to use both tricks. They solve different problems and can work well together.
One way to think about it is that weight decay changes the function that's being optimized, while m | Neural Networks: weight change momentum and weight decay
Yes, it's very common to use both tricks. They solve different problems and can work well together.
One way to think about it is that weight decay changes the function that's being optimized, while momentum changes the path you take to the optimum.
Weight decay,... | Neural Networks: weight change momentum and weight decay
Yes, it's very common to use both tricks. They solve different problems and can work well together.
One way to think about it is that weight decay changes the function that's being optimized, while m |
5,583 | What is the adjusted R-squared formula in lm in R and how should it be interpreted? | 1. What formula does lm in R use for adjusted r-square?
As already mentioned, typing summary.lm will give you the code that R uses to calculate adjusted R square. Extracting the most relevant line you get:
ans$adj.r.squared <- 1 - (1 - ans$r.squared) * ((n - df.int)/rdf)
which corresponds in mathematical notation to:
... | What is the adjusted R-squared formula in lm in R and how should it be interpreted? | 1. What formula does lm in R use for adjusted r-square?
As already mentioned, typing summary.lm will give you the code that R uses to calculate adjusted R square. Extracting the most relevant line you | What is the adjusted R-squared formula in lm in R and how should it be interpreted?
1. What formula does lm in R use for adjusted r-square?
As already mentioned, typing summary.lm will give you the code that R uses to calculate adjusted R square. Extracting the most relevant line you get:
ans$adj.r.squared <- 1 - (1 - ... | What is the adjusted R-squared formula in lm in R and how should it be interpreted?
1. What formula does lm in R use for adjusted r-square?
As already mentioned, typing summary.lm will give you the code that R uses to calculate adjusted R square. Extracting the most relevant line you |
5,584 | What is the adjusted R-squared formula in lm in R and how should it be interpreted? | Regarding your first question: If you don't know how it is calculated look at the code! If you type summary.lm in your console, you get the code for this function. If you skim throught the code you'll find a line: ans$adj.r.squared <- 1 - (1 - ans$r.squared) * ((n - df.int)/rdf). If you look some lines above of this li... | What is the adjusted R-squared formula in lm in R and how should it be interpreted? | Regarding your first question: If you don't know how it is calculated look at the code! If you type summary.lm in your console, you get the code for this function. If you skim throught the code you'll | What is the adjusted R-squared formula in lm in R and how should it be interpreted?
Regarding your first question: If you don't know how it is calculated look at the code! If you type summary.lm in your console, you get the code for this function. If you skim throught the code you'll find a line: ans$adj.r.squared <- 1... | What is the adjusted R-squared formula in lm in R and how should it be interpreted?
Regarding your first question: If you don't know how it is calculated look at the code! If you type summary.lm in your console, you get the code for this function. If you skim throught the code you'll |
5,585 | Poisson regression to estimate relative risk for binary outcomes | An answer to all four of your questions, preceeded by a note:
It's not actually all that common for modern epidemiology studies to report an odds ratio from a logistic regression for a cohort study. It remains the regression technique of choice for case-control studies, but more sophisticated techniques are now the de ... | Poisson regression to estimate relative risk for binary outcomes | An answer to all four of your questions, preceeded by a note:
It's not actually all that common for modern epidemiology studies to report an odds ratio from a logistic regression for a cohort study. I | Poisson regression to estimate relative risk for binary outcomes
An answer to all four of your questions, preceeded by a note:
It's not actually all that common for modern epidemiology studies to report an odds ratio from a logistic regression for a cohort study. It remains the regression technique of choice for case-c... | Poisson regression to estimate relative risk for binary outcomes
An answer to all four of your questions, preceeded by a note:
It's not actually all that common for modern epidemiology studies to report an odds ratio from a logistic regression for a cohort study. I |
5,586 | Poisson regression to estimate relative risk for binary outcomes | I too speculate at the prevalence of logistic models in the literature when a relative risk model would be more appropriate. We as statisticians are all too familiar with adherence to convention or sticking to "drop-down-menu" analyses. These create far more problems than they solve. Logistic regression is taught as a ... | Poisson regression to estimate relative risk for binary outcomes | I too speculate at the prevalence of logistic models in the literature when a relative risk model would be more appropriate. We as statisticians are all too familiar with adherence to convention or st | Poisson regression to estimate relative risk for binary outcomes
I too speculate at the prevalence of logistic models in the literature when a relative risk model would be more appropriate. We as statisticians are all too familiar with adherence to convention or sticking to "drop-down-menu" analyses. These create far m... | Poisson regression to estimate relative risk for binary outcomes
I too speculate at the prevalence of logistic models in the literature when a relative risk model would be more appropriate. We as statisticians are all too familiar with adherence to convention or st |
5,587 | How can I test whether a random effect is significant? | The estimate ID's variance = 0, indicates that the level of
between-group variability is not sufficient to warrant incorporating random effects in the model; i.e., your model is degenerate.
As you correctly identify yourself: most probably, yes; ID as a random effect is unnecessary. A few things spring to mind to test ... | How can I test whether a random effect is significant? | The estimate ID's variance = 0, indicates that the level of
between-group variability is not sufficient to warrant incorporating random effects in the model; i.e., your model is degenerate.
As you cor | How can I test whether a random effect is significant?
The estimate ID's variance = 0, indicates that the level of
between-group variability is not sufficient to warrant incorporating random effects in the model; i.e., your model is degenerate.
As you correctly identify yourself: most probably, yes; ID as a random effe... | How can I test whether a random effect is significant?
The estimate ID's variance = 0, indicates that the level of
between-group variability is not sufficient to warrant incorporating random effects in the model; i.e., your model is degenerate.
As you cor |
5,588 | How can I test whether a random effect is significant? | I'm not sure that the approach I'm going to suggest is reasonable, so those who know more about this topic correct me if I'm wrong.
My proposal is to create an additional column in your data that has a constant value of 1:
IDconst <- factor(rep(1, each=length(tv$Velocity)))
Then, you can create a model that uses this ... | How can I test whether a random effect is significant? | I'm not sure that the approach I'm going to suggest is reasonable, so those who know more about this topic correct me if I'm wrong.
My proposal is to create an additional column in your data that has | How can I test whether a random effect is significant?
I'm not sure that the approach I'm going to suggest is reasonable, so those who know more about this topic correct me if I'm wrong.
My proposal is to create an additional column in your data that has a constant value of 1:
IDconst <- factor(rep(1, each=length(tv$Ve... | How can I test whether a random effect is significant?
I'm not sure that the approach I'm going to suggest is reasonable, so those who know more about this topic correct me if I'm wrong.
My proposal is to create an additional column in your data that has |
5,589 | Computing Cohen's Kappa variance (and standard errors) | I don't know which of the two ways to calculate the variance is to prefer but I can give you a third, practical and useful way to calculate confidence/credible intervals by using Bayesian estimation of Cohen's Kappa.
The R and JAGS code below generates MCMC samples from the posterior distribution of the credible values... | Computing Cohen's Kappa variance (and standard errors) | I don't know which of the two ways to calculate the variance is to prefer but I can give you a third, practical and useful way to calculate confidence/credible intervals by using Bayesian estimation o | Computing Cohen's Kappa variance (and standard errors)
I don't know which of the two ways to calculate the variance is to prefer but I can give you a third, practical and useful way to calculate confidence/credible intervals by using Bayesian estimation of Cohen's Kappa.
The R and JAGS code below generates MCMC samples... | Computing Cohen's Kappa variance (and standard errors)
I don't know which of the two ways to calculate the variance is to prefer but I can give you a third, practical and useful way to calculate confidence/credible intervals by using Bayesian estimation o |
5,590 | How well can multiple regression really "control for" covariates? | There is a becoming widely accepted, non-statistical perhaps, answer to - what assumptions does one need to make to claim one has really controlled for the covariates.
That can be done with Judea Pearl's causal graphs and do calculus.
See http://ftp.cs.ucla.edu/pub/stat_ser/r402.pdf as well as other material on his ... | How well can multiple regression really "control for" covariates? | There is a becoming widely accepted, non-statistical perhaps, answer to - what assumptions does one need to make to claim one has really controlled for the covariates.
That can be done with Judea Pea | How well can multiple regression really "control for" covariates?
There is a becoming widely accepted, non-statistical perhaps, answer to - what assumptions does one need to make to claim one has really controlled for the covariates.
That can be done with Judea Pearl's causal graphs and do calculus.
See http://ftp.cs... | How well can multiple regression really "control for" covariates?
There is a becoming widely accepted, non-statistical perhaps, answer to - what assumptions does one need to make to claim one has really controlled for the covariates.
That can be done with Judea Pea |
5,591 | How well can multiple regression really "control for" covariates? | Answer to question 1:
The magnitude of seriousness is best assessed in a contextual way
(i.e., should consider all factors contributing to validity).
The magnitude of seriousness should not be assessed in a categorical way. An example is the notion of a hierarchy of inference for study designs (e.g. case reports are ... | How well can multiple regression really "control for" covariates? | Answer to question 1:
The magnitude of seriousness is best assessed in a contextual way
(i.e., should consider all factors contributing to validity).
The magnitude of seriousness should not be asses | How well can multiple regression really "control for" covariates?
Answer to question 1:
The magnitude of seriousness is best assessed in a contextual way
(i.e., should consider all factors contributing to validity).
The magnitude of seriousness should not be assessed in a categorical way. An example is the notion of ... | How well can multiple regression really "control for" covariates?
Answer to question 1:
The magnitude of seriousness is best assessed in a contextual way
(i.e., should consider all factors contributing to validity).
The magnitude of seriousness should not be asses |
5,592 | How to plot trends properly | Sometimes less is more. With less detail about the year-to-year variations and the country distinctions you can provide more information about the trends. Since the other countries are moving mostly together you can get by without separate colors.
In using a smoother you're requiring the reader to trust that you haven'... | How to plot trends properly | Sometimes less is more. With less detail about the year-to-year variations and the country distinctions you can provide more information about the trends. Since the other countries are moving mostly t | How to plot trends properly
Sometimes less is more. With less detail about the year-to-year variations and the country distinctions you can provide more information about the trends. Since the other countries are moving mostly together you can get by without separate colors.
In using a smoother you're requiring the rea... | How to plot trends properly
Sometimes less is more. With less detail about the year-to-year variations and the country distinctions you can provide more information about the trends. Since the other countries are moving mostly t |
5,593 | How to plot trends properly | There are good answers here. Let me take you at your word that you want to show that the trend for Germany differs from the rest. Levels vs. changes is a common distinction in economics. Your data are in levels, but your question is stated as seeking changes. The way to do that is to set the reference level (here 1... | How to plot trends properly | There are good answers here. Let me take you at your word that you want to show that the trend for Germany differs from the rest. Levels vs. changes is a common distinction in economics. Your data | How to plot trends properly
There are good answers here. Let me take you at your word that you want to show that the trend for Germany differs from the rest. Levels vs. changes is a common distinction in economics. Your data are in levels, but your question is stated as seeking changes. The way to do that is to set... | How to plot trends properly
There are good answers here. Let me take you at your word that you want to show that the trend for Germany differs from the rest. Levels vs. changes is a common distinction in economics. Your data |
5,594 | How to plot trends properly | There are many good ideas here in other answers, but they don't exhaust the good solutions that are possible. The first graph in this answer takes it that different levels of death rate can be discussed and explained separately. In allowing each series to fill much of the space available, it focuses readers' attention ... | How to plot trends properly | There are many good ideas here in other answers, but they don't exhaust the good solutions that are possible. The first graph in this answer takes it that different levels of death rate can be discuss | How to plot trends properly
There are many good ideas here in other answers, but they don't exhaust the good solutions that are possible. The first graph in this answer takes it that different levels of death rate can be discussed and explained separately. In allowing each series to fill much of the space available, it... | How to plot trends properly
There are many good ideas here in other answers, but they don't exhaust the good solutions that are possible. The first graph in this answer takes it that different levels of death rate can be discuss |
5,595 | How to plot trends properly | Your graph is reasonable, but it would require some refinement, including a title, axis labels, and complete country labels. If your goal is to stress the fact that Germany was the only country with a rise in death rate over the observation period then a simple way to do this would be to highlight this line in the plo... | How to plot trends properly | Your graph is reasonable, but it would require some refinement, including a title, axis labels, and complete country labels. If your goal is to stress the fact that Germany was the only country with | How to plot trends properly
Your graph is reasonable, but it would require some refinement, including a title, axis labels, and complete country labels. If your goal is to stress the fact that Germany was the only country with a rise in death rate over the observation period then a simple way to do this would be to hi... | How to plot trends properly
Your graph is reasonable, but it would require some refinement, including a title, axis labels, and complete country labels. If your goal is to stress the fact that Germany was the only country with |
5,596 | How to plot trends properly | Although the stated objective is to display changes, apparently you wish to show the annual time series by country, too. That suggests not completely redoing the graphic, but just modifying it.
Since a change concerns what happens from one year to the next, you might consider representing the changes by graphical symb... | How to plot trends properly | Although the stated objective is to display changes, apparently you wish to show the annual time series by country, too. That suggests not completely redoing the graphic, but just modifying it.
Since | How to plot trends properly
Although the stated objective is to display changes, apparently you wish to show the annual time series by country, too. That suggests not completely redoing the graphic, but just modifying it.
Since a change concerns what happens from one year to the next, you might consider representing t... | How to plot trends properly
Although the stated objective is to display changes, apparently you wish to show the annual time series by country, too. That suggests not completely redoing the graphic, but just modifying it.
Since |
5,597 | How to plot trends properly | Slopegraphs
One way that you could present your data is using a slopegraph which is particular good for comparing changes or gradients (some links: 1 2 )
Below is
On the left an example of a slopegraph that shows how this looks for your case.
In the center a more complex slopegraph which also shows the year 1932
On ... | How to plot trends properly | Slopegraphs
One way that you could present your data is using a slopegraph which is particular good for comparing changes or gradients (some links: 1 2 )
Below is
On the left an example of a slopegra | How to plot trends properly
Slopegraphs
One way that you could present your data is using a slopegraph which is particular good for comparing changes or gradients (some links: 1 2 )
Below is
On the left an example of a slopegraph that shows how this looks for your case.
In the center a more complex slopegraph which a... | How to plot trends properly
Slopegraphs
One way that you could present your data is using a slopegraph which is particular good for comparing changes or gradients (some links: 1 2 )
Below is
On the left an example of a slopegra |
5,598 | How to plot trends properly | If you are wanting to highlight change, then perhaps calculate this and display that. Using a heatmap to display the changes can be useful as it allows comparisons to be made without overplotting issues and avoids interpolation issues that can come from line graphs.
Using your data as d in R:
library(tidyverse)
d2 <-... | How to plot trends properly | If you are wanting to highlight change, then perhaps calculate this and display that. Using a heatmap to display the changes can be useful as it allows comparisons to be made without overplotting issu | How to plot trends properly
If you are wanting to highlight change, then perhaps calculate this and display that. Using a heatmap to display the changes can be useful as it allows comparisons to be made without overplotting issues and avoids interpolation issues that can come from line graphs.
Using your data as d in R... | How to plot trends properly
If you are wanting to highlight change, then perhaps calculate this and display that. Using a heatmap to display the changes can be useful as it allows comparisons to be made without overplotting issu |
5,599 | How to plot trends properly | Depends on the audience, but I would simplify things:
Then spell it out in the caption e.g.
From 1932-37, the annual death rate increased in Germany, whereas it fell overall throughout central Europe (France, Belgium, Netherlands, Denmark, Austria, Czech Republic, Poland).
(BTW what is ch vs. cz i.e. which country a... | How to plot trends properly | Depends on the audience, but I would simplify things:
Then spell it out in the caption e.g.
From 1932-37, the annual death rate increased in Germany, whereas it fell overall throughout central Europ | How to plot trends properly
Depends on the audience, but I would simplify things:
Then spell it out in the caption e.g.
From 1932-37, the annual death rate increased in Germany, whereas it fell overall throughout central Europe (France, Belgium, Netherlands, Denmark, Austria, Czech Republic, Poland).
(BTW what is ch... | How to plot trends properly
Depends on the audience, but I would simplify things:
Then spell it out in the caption e.g.
From 1932-37, the annual death rate increased in Germany, whereas it fell overall throughout central Europ |
5,600 | How to plot trends properly | Here I show you the difference of the logarithm of the ratio of death per 1000 inhabitants, with regards to the previous year (therefore 1927 is not shown). Germany is shown in red while the average of other countries is shown in the thick black line.
Germany had increases in the ratio in 5 out of 10 years. After 1932... | How to plot trends properly | Here I show you the difference of the logarithm of the ratio of death per 1000 inhabitants, with regards to the previous year (therefore 1927 is not shown). Germany is shown in red while the average o | How to plot trends properly
Here I show you the difference of the logarithm of the ratio of death per 1000 inhabitants, with regards to the previous year (therefore 1927 is not shown). Germany is shown in red while the average of other countries is shown in the thick black line.
Germany had increases in the ratio in 5... | How to plot trends properly
Here I show you the difference of the logarithm of the ratio of death per 1000 inhabitants, with regards to the previous year (therefore 1927 is not shown). Germany is shown in red while the average o |
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