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 |
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4,301 | Is the COVID-19 pandemic curve a Gaussian curve? | Not but (under the right assumptions that in practice aren't likely to hold) sort of.
As Michael Reid points the number of infected people of an epidemic under simplified constant conditions (constant R0) is governed by the logistic equation, which leads to a sigmoid, the logistic function. The derivative of the logist... | Is the COVID-19 pandemic curve a Gaussian curve? | Not but (under the right assumptions that in practice aren't likely to hold) sort of.
As Michael Reid points the number of infected people of an epidemic under simplified constant conditions (constant | Is the COVID-19 pandemic curve a Gaussian curve?
Not but (under the right assumptions that in practice aren't likely to hold) sort of.
As Michael Reid points the number of infected people of an epidemic under simplified constant conditions (constant R0) is governed by the logistic equation, which leads to a sigmoid, th... | Is the COVID-19 pandemic curve a Gaussian curve?
Not but (under the right assumptions that in practice aren't likely to hold) sort of.
As Michael Reid points the number of infected people of an epidemic under simplified constant conditions (constant |
4,302 | Is the COVID-19 pandemic curve a Gaussian curve? | Short answer, no. I was wondering the same thing and I found out a way to plot populations of susceptible, infected, and recovered people. It's a model called a compartmental model of epidemiology and the specific algorithm is called the Gillespie Algorithm. There's Python code in the second link but I tried it in R ... | Is the COVID-19 pandemic curve a Gaussian curve? | Short answer, no. I was wondering the same thing and I found out a way to plot populations of susceptible, infected, and recovered people. It's a model called a compartmental model of epidemiology an | Is the COVID-19 pandemic curve a Gaussian curve?
Short answer, no. I was wondering the same thing and I found out a way to plot populations of susceptible, infected, and recovered people. It's a model called a compartmental model of epidemiology and the specific algorithm is called the Gillespie Algorithm. There's Py... | Is the COVID-19 pandemic curve a Gaussian curve?
Short answer, no. I was wondering the same thing and I found out a way to plot populations of susceptible, infected, and recovered people. It's a model called a compartmental model of epidemiology an |
4,303 | Is the COVID-19 pandemic curve a Gaussian curve? | The most simple analysis of an epidemic leads to a logistics curve model. The rate of new infections will be the derivative of total cases, which under that model would give a bell-shaped curve (normal-ish in the middle but with much fatter tails -- see Dirk's comment below).
The assumptions behind the model are a cons... | Is the COVID-19 pandemic curve a Gaussian curve? | The most simple analysis of an epidemic leads to a logistics curve model. The rate of new infections will be the derivative of total cases, which under that model would give a bell-shaped curve (norma | Is the COVID-19 pandemic curve a Gaussian curve?
The most simple analysis of an epidemic leads to a logistics curve model. The rate of new infections will be the derivative of total cases, which under that model would give a bell-shaped curve (normal-ish in the middle but with much fatter tails -- see Dirk's comment be... | Is the COVID-19 pandemic curve a Gaussian curve?
The most simple analysis of an epidemic leads to a logistics curve model. The rate of new infections will be the derivative of total cases, which under that model would give a bell-shaped curve (norma |
4,304 | Is the COVID-19 pandemic curve a Gaussian curve? | I'm no epidemiologist myself, but another key difference between that curve and a Gaussian curve is that the Gaussian decays to zero relatively fast (as $e^{-t^2}$ after some time $t$), while an actual epidemic can be expected to taper off at a much slower rate at the end, or might even not decay to $0$ but to some oth... | Is the COVID-19 pandemic curve a Gaussian curve? | I'm no epidemiologist myself, but another key difference between that curve and a Gaussian curve is that the Gaussian decays to zero relatively fast (as $e^{-t^2}$ after some time $t$), while an actua | Is the COVID-19 pandemic curve a Gaussian curve?
I'm no epidemiologist myself, but another key difference between that curve and a Gaussian curve is that the Gaussian decays to zero relatively fast (as $e^{-t^2}$ after some time $t$), while an actual epidemic can be expected to taper off at a much slower rate at the en... | Is the COVID-19 pandemic curve a Gaussian curve?
I'm no epidemiologist myself, but another key difference between that curve and a Gaussian curve is that the Gaussian decays to zero relatively fast (as $e^{-t^2}$ after some time $t$), while an actua |
4,305 | Is the COVID-19 pandemic curve a Gaussian curve? | No. As demonstrated here on various countries, so far, a reasonable way to model the curves of daily new confirmed cases and deaths for Covid-19 is to use:
an increasing exponential at the very beginning
a logistic curve when the curve starts to flatten (see 3Blue1Brown's video)
an decreasing exponential shortly afte... | Is the COVID-19 pandemic curve a Gaussian curve? | No. As demonstrated here on various countries, so far, a reasonable way to model the curves of daily new confirmed cases and deaths for Covid-19 is to use:
an increasing exponential at the very begin | Is the COVID-19 pandemic curve a Gaussian curve?
No. As demonstrated here on various countries, so far, a reasonable way to model the curves of daily new confirmed cases and deaths for Covid-19 is to use:
an increasing exponential at the very beginning
a logistic curve when the curve starts to flatten (see 3Blue1Brown... | Is the COVID-19 pandemic curve a Gaussian curve?
No. As demonstrated here on various countries, so far, a reasonable way to model the curves of daily new confirmed cases and deaths for Covid-19 is to use:
an increasing exponential at the very begin |
4,306 | Is the COVID-19 pandemic curve a Gaussian curve? | In fact, this curve seems to fit well an Inverse Gausssian distribution. This distribution is widely used in psychology or economics for describing the distribution of time delays. Indeed, there are similarities of such processes with a pandemic (where what is denoted in the graph by the variable $x$ will be time since... | Is the COVID-19 pandemic curve a Gaussian curve? | In fact, this curve seems to fit well an Inverse Gausssian distribution. This distribution is widely used in psychology or economics for describing the distribution of time delays. Indeed, there are s | Is the COVID-19 pandemic curve a Gaussian curve?
In fact, this curve seems to fit well an Inverse Gausssian distribution. This distribution is widely used in psychology or economics for describing the distribution of time delays. Indeed, there are similarities of such processes with a pandemic (where what is denoted in... | Is the COVID-19 pandemic curve a Gaussian curve?
In fact, this curve seems to fit well an Inverse Gausssian distribution. This distribution is widely used in psychology or economics for describing the distribution of time delays. Indeed, there are s |
4,307 | Is the COVID-19 pandemic curve a Gaussian curve? | In the early stages of an epidemic growth is exponential. The two key parameters are R0 (average number of people infected by each person who catches it) and incubation time. The goal is to reduce R0 - once it is less than 1.0 the epidemic is over. Most counties are still at that stage for COVID-19.
Once a significant ... | Is the COVID-19 pandemic curve a Gaussian curve? | In the early stages of an epidemic growth is exponential. The two key parameters are R0 (average number of people infected by each person who catches it) and incubation time. The goal is to reduce R0 | Is the COVID-19 pandemic curve a Gaussian curve?
In the early stages of an epidemic growth is exponential. The two key parameters are R0 (average number of people infected by each person who catches it) and incubation time. The goal is to reduce R0 - once it is less than 1.0 the epidemic is over. Most counties are stil... | Is the COVID-19 pandemic curve a Gaussian curve?
In the early stages of an epidemic growth is exponential. The two key parameters are R0 (average number of people infected by each person who catches it) and incubation time. The goal is to reduce R0 |
4,308 | Is the COVID-19 pandemic curve a Gaussian curve? | Biological growth (cumulative) of virus epidemics, or trees, or humans, or other biological phenomena, in general follows the logistic function: 1/(1+e^-1). The logistic curve is sigmoid or S-shaped. It does not "flatten" but it has an inflection point.
The first derivative is the growth rate. That curve follows the lo... | Is the COVID-19 pandemic curve a Gaussian curve? | Biological growth (cumulative) of virus epidemics, or trees, or humans, or other biological phenomena, in general follows the logistic function: 1/(1+e^-1). The logistic curve is sigmoid or S-shaped. | Is the COVID-19 pandemic curve a Gaussian curve?
Biological growth (cumulative) of virus epidemics, or trees, or humans, or other biological phenomena, in general follows the logistic function: 1/(1+e^-1). The logistic curve is sigmoid or S-shaped. It does not "flatten" but it has an inflection point.
The first derivat... | Is the COVID-19 pandemic curve a Gaussian curve?
Biological growth (cumulative) of virus epidemics, or trees, or humans, or other biological phenomena, in general follows the logistic function: 1/(1+e^-1). The logistic curve is sigmoid or S-shaped. |
4,309 | What are the breakthroughs in Statistics of the past 15 years? | The answer is so simple that i have to write all this gibberish to make CV let me post it: R | What are the breakthroughs in Statistics of the past 15 years? | The answer is so simple that i have to write all this gibberish to make CV let me post it: R | What are the breakthroughs in Statistics of the past 15 years?
The answer is so simple that i have to write all this gibberish to make CV let me post it: R | What are the breakthroughs in Statistics of the past 15 years?
The answer is so simple that i have to write all this gibberish to make CV let me post it: R |
4,310 | What are the breakthroughs in Statistics of the past 15 years? | I'm not sure if you would call it a "breakthrough" per se, But the Publishing of Probability Theory: The Logic of Science By Edwin Jaynes and Larry Bretthorst may be noteworthy. Some of the things they do here are:
1) show equivalence between some iterative "seasonal adjustment" schemes and Bayesian "nuisance paramete... | What are the breakthroughs in Statistics of the past 15 years? | I'm not sure if you would call it a "breakthrough" per se, But the Publishing of Probability Theory: The Logic of Science By Edwin Jaynes and Larry Bretthorst may be noteworthy. Some of the things th | What are the breakthroughs in Statistics of the past 15 years?
I'm not sure if you would call it a "breakthrough" per se, But the Publishing of Probability Theory: The Logic of Science By Edwin Jaynes and Larry Bretthorst may be noteworthy. Some of the things they do here are:
1) show equivalence between some iterativ... | What are the breakthroughs in Statistics of the past 15 years?
I'm not sure if you would call it a "breakthrough" per se, But the Publishing of Probability Theory: The Logic of Science By Edwin Jaynes and Larry Bretthorst may be noteworthy. Some of the things th |
4,311 | What are the breakthroughs in Statistics of the past 15 years? | As an applied statistician and occasional minor software author, I'd say:
WinBUGS (released 1997)
It's based on BUGS, which was released more than 15 years ago (1989), but it's WinBUGS that made Bayesian analysis of realistically complex models available to a far wider user base. See e.g. Lunn, Spiegelhalter, Thomas ... | What are the breakthroughs in Statistics of the past 15 years? | As an applied statistician and occasional minor software author, I'd say:
WinBUGS (released 1997)
It's based on BUGS, which was released more than 15 years ago (1989), but it's WinBUGS that made Bay | What are the breakthroughs in Statistics of the past 15 years?
As an applied statistician and occasional minor software author, I'd say:
WinBUGS (released 1997)
It's based on BUGS, which was released more than 15 years ago (1989), but it's WinBUGS that made Bayesian analysis of realistically complex models available ... | What are the breakthroughs in Statistics of the past 15 years?
As an applied statistician and occasional minor software author, I'd say:
WinBUGS (released 1997)
It's based on BUGS, which was released more than 15 years ago (1989), but it's WinBUGS that made Bay |
4,312 | What are the breakthroughs in Statistics of the past 15 years? | LARS gets my vote. It combines linear regression with variable selection. Algorithms to compute it usually give you a collection of $k$ linear models, the $i$th one of which has nonzero coefficients for only $i$ regressors, so you can easily look at models of different complexity. | What are the breakthroughs in Statistics of the past 15 years? | LARS gets my vote. It combines linear regression with variable selection. Algorithms to compute it usually give you a collection of $k$ linear models, the $i$th one of which has nonzero coefficients f | What are the breakthroughs in Statistics of the past 15 years?
LARS gets my vote. It combines linear regression with variable selection. Algorithms to compute it usually give you a collection of $k$ linear models, the $i$th one of which has nonzero coefficients for only $i$ regressors, so you can easily look at models ... | What are the breakthroughs in Statistics of the past 15 years?
LARS gets my vote. It combines linear regression with variable selection. Algorithms to compute it usually give you a collection of $k$ linear models, the $i$th one of which has nonzero coefficients f |
4,313 | What are the breakthroughs in Statistics of the past 15 years? | The introduction of the "intrinsic discrepancy" loss function and other "parameterisation free" loss functions into decision theory. It has many other "nice" properties, but I think the best one is as follows:
if the best estimate of $\theta$ using the intrinsic discrepancy loss function is $\theta^{e}$, then the bes... | What are the breakthroughs in Statistics of the past 15 years? | The introduction of the "intrinsic discrepancy" loss function and other "parameterisation free" loss functions into decision theory. It has many other "nice" properties, but I think the best one is a | What are the breakthroughs in Statistics of the past 15 years?
The introduction of the "intrinsic discrepancy" loss function and other "parameterisation free" loss functions into decision theory. It has many other "nice" properties, but I think the best one is as follows:
if the best estimate of $\theta$ using the in... | What are the breakthroughs in Statistics of the past 15 years?
The introduction of the "intrinsic discrepancy" loss function and other "parameterisation free" loss functions into decision theory. It has many other "nice" properties, but I think the best one is a |
4,314 | What are the breakthroughs in Statistics of the past 15 years? | Just falling within the 15 year window, I believe, are the algorithms for controlling False Discovery Rate. I like the 'q-value' approach. | What are the breakthroughs in Statistics of the past 15 years? | Just falling within the 15 year window, I believe, are the algorithms for controlling False Discovery Rate. I like the 'q-value' approach. | What are the breakthroughs in Statistics of the past 15 years?
Just falling within the 15 year window, I believe, are the algorithms for controlling False Discovery Rate. I like the 'q-value' approach. | What are the breakthroughs in Statistics of the past 15 years?
Just falling within the 15 year window, I believe, are the algorithms for controlling False Discovery Rate. I like the 'q-value' approach. |
4,315 | What are the breakthroughs in Statistics of the past 15 years? | Adding my own 5 cents, I believe the most significant breakthrough of the past 15 years has been Compressed Sensing. LARS, LASSO, and a host of other algorithms fall in this domain, in that Compressed Sensing explains why they work and extends them to other domains. | What are the breakthroughs in Statistics of the past 15 years? | Adding my own 5 cents, I believe the most significant breakthrough of the past 15 years has been Compressed Sensing. LARS, LASSO, and a host of other algorithms fall in this domain, in that Compressed | What are the breakthroughs in Statistics of the past 15 years?
Adding my own 5 cents, I believe the most significant breakthrough of the past 15 years has been Compressed Sensing. LARS, LASSO, and a host of other algorithms fall in this domain, in that Compressed Sensing explains why they work and extends them to other... | What are the breakthroughs in Statistics of the past 15 years?
Adding my own 5 cents, I believe the most significant breakthrough of the past 15 years has been Compressed Sensing. LARS, LASSO, and a host of other algorithms fall in this domain, in that Compressed |
4,316 | What are the breakthroughs in Statistics of the past 15 years? | Something that has very little to do with statistics themselves, but has been massively beneficial: The increasing firepower of computers, making larger datasets and more complex statistical analysis more accessible, especially in applied fields. | What are the breakthroughs in Statistics of the past 15 years? | Something that has very little to do with statistics themselves, but has been massively beneficial: The increasing firepower of computers, making larger datasets and more complex statistical analysis | What are the breakthroughs in Statistics of the past 15 years?
Something that has very little to do with statistics themselves, but has been massively beneficial: The increasing firepower of computers, making larger datasets and more complex statistical analysis more accessible, especially in applied fields. | What are the breakthroughs in Statistics of the past 15 years?
Something that has very little to do with statistics themselves, but has been massively beneficial: The increasing firepower of computers, making larger datasets and more complex statistical analysis |
4,317 | What are the breakthroughs in Statistics of the past 15 years? | The Expectation-Propagation algorithm for Bayesian inference, especially in Gaussian Process classification, was arguably a significant breakthrough, as it provides an efficient analytic approximation method that works almost as well as computationally expensive sampling based approaches (unlike the usual Laplace appro... | What are the breakthroughs in Statistics of the past 15 years? | The Expectation-Propagation algorithm for Bayesian inference, especially in Gaussian Process classification, was arguably a significant breakthrough, as it provides an efficient analytic approximation | What are the breakthroughs in Statistics of the past 15 years?
The Expectation-Propagation algorithm for Bayesian inference, especially in Gaussian Process classification, was arguably a significant breakthrough, as it provides an efficient analytic approximation method that works almost as well as computationally expe... | What are the breakthroughs in Statistics of the past 15 years?
The Expectation-Propagation algorithm for Bayesian inference, especially in Gaussian Process classification, was arguably a significant breakthrough, as it provides an efficient analytic approximation |
4,318 | What are the breakthroughs in Statistics of the past 15 years? | I think that the 'Approximate Bayesian Inference for Latent Gaussian
Models Using Integrated Nested Laplace Approximations' of H. Rue et. al (2009) is a potential candidate. | What are the breakthroughs in Statistics of the past 15 years? | I think that the 'Approximate Bayesian Inference for Latent Gaussian
Models Using Integrated Nested Laplace Approximations' of H. Rue et. al (2009) is a potential candidate. | What are the breakthroughs in Statistics of the past 15 years?
I think that the 'Approximate Bayesian Inference for Latent Gaussian
Models Using Integrated Nested Laplace Approximations' of H. Rue et. al (2009) is a potential candidate. | What are the breakthroughs in Statistics of the past 15 years?
I think that the 'Approximate Bayesian Inference for Latent Gaussian
Models Using Integrated Nested Laplace Approximations' of H. Rue et. al (2009) is a potential candidate. |
4,319 | What are the breakthroughs in Statistics of the past 15 years? | In my opinion, everything allowing you to run new models on a large scale is a breakthrough. Kernel Interpolation for Scalable Structured Gaussian Processes (KISS-GP) could be a candidate (though the idea is new and there have not been many implementations of the idea presented). | What are the breakthroughs in Statistics of the past 15 years? | In my opinion, everything allowing you to run new models on a large scale is a breakthrough. Kernel Interpolation for Scalable Structured Gaussian Processes (KISS-GP) could be a candidate (though the | What are the breakthroughs in Statistics of the past 15 years?
In my opinion, everything allowing you to run new models on a large scale is a breakthrough. Kernel Interpolation for Scalable Structured Gaussian Processes (KISS-GP) could be a candidate (though the idea is new and there have not been many implementations ... | What are the breakthroughs in Statistics of the past 15 years?
In my opinion, everything allowing you to run new models on a large scale is a breakthrough. Kernel Interpolation for Scalable Structured Gaussian Processes (KISS-GP) could be a candidate (though the |
4,320 | What are the breakthroughs in Statistics of the past 15 years? | In my opinion, paper published in 2011 in Science magazine. Authors propose very interesting measure of association between pair of random variables that works well in many situations where similar measures fail (Pearson, Spearman, Kendall). Really nice paper. Here it is. | What are the breakthroughs in Statistics of the past 15 years? | In my opinion, paper published in 2011 in Science magazine. Authors propose very interesting measure of association between pair of random variables that works well in many situations where similar me | What are the breakthroughs in Statistics of the past 15 years?
In my opinion, paper published in 2011 in Science magazine. Authors propose very interesting measure of association between pair of random variables that works well in many situations where similar measures fail (Pearson, Spearman, Kendall). Really nice pap... | What are the breakthroughs in Statistics of the past 15 years?
In my opinion, paper published in 2011 in Science magazine. Authors propose very interesting measure of association between pair of random variables that works well in many situations where similar me |
4,321 | What are the breakthroughs in Statistics of the past 15 years? | While a bit more general than statistics, I think there have been important advances in methods of reproducible research (RR). For example the development of R's knittr and Sweave packages and "R Markdown" notebooks, LyX and LaTeX improvements have contributed significantly to data sharing, collaboration, verification... | What are the breakthroughs in Statistics of the past 15 years? | While a bit more general than statistics, I think there have been important advances in methods of reproducible research (RR). For example the development of R's knittr and Sweave packages and "R Mar | What are the breakthroughs in Statistics of the past 15 years?
While a bit more general than statistics, I think there have been important advances in methods of reproducible research (RR). For example the development of R's knittr and Sweave packages and "R Markdown" notebooks, LyX and LaTeX improvements have contrib... | What are the breakthroughs in Statistics of the past 15 years?
While a bit more general than statistics, I think there have been important advances in methods of reproducible research (RR). For example the development of R's knittr and Sweave packages and "R Mar |
4,322 | Why continue to teach and use hypothesis testing (when confidence intervals are available)? | This is my personal opinion, so I'm not sure it properly qualifies as an answer.
Why should we teach hypothesis testing?
One very big reason, in short, is that, in all likelihood, in the time it takes you to read this sentence, hundreds, if not thousands (or millions) of hypothesis tests have been conducted within a 10... | Why continue to teach and use hypothesis testing (when confidence intervals are available)? | This is my personal opinion, so I'm not sure it properly qualifies as an answer.
Why should we teach hypothesis testing?
One very big reason, in short, is that, in all likelihood, in the time it takes | Why continue to teach and use hypothesis testing (when confidence intervals are available)?
This is my personal opinion, so I'm not sure it properly qualifies as an answer.
Why should we teach hypothesis testing?
One very big reason, in short, is that, in all likelihood, in the time it takes you to read this sentence, ... | Why continue to teach and use hypothesis testing (when confidence intervals are available)?
This is my personal opinion, so I'm not sure it properly qualifies as an answer.
Why should we teach hypothesis testing?
One very big reason, in short, is that, in all likelihood, in the time it takes |
4,323 | Why continue to teach and use hypothesis testing (when confidence intervals are available)? | I teach hypothesis tests for a number of reasons. One is historical, that they'll have to understand a large body of prior research they read and understand the hypothesis testing point of view. A second is that, even in modern times, it's still used by some researchers, often implicitly, when performing other kinds ... | Why continue to teach and use hypothesis testing (when confidence intervals are available)? | I teach hypothesis tests for a number of reasons. One is historical, that they'll have to understand a large body of prior research they read and understand the hypothesis testing point of view. A s | Why continue to teach and use hypothesis testing (when confidence intervals are available)?
I teach hypothesis tests for a number of reasons. One is historical, that they'll have to understand a large body of prior research they read and understand the hypothesis testing point of view. A second is that, even in moder... | Why continue to teach and use hypothesis testing (when confidence intervals are available)?
I teach hypothesis tests for a number of reasons. One is historical, that they'll have to understand a large body of prior research they read and understand the hypothesis testing point of view. A s |
4,324 | Why continue to teach and use hypothesis testing (when confidence intervals are available)? | I personally feel we would be better off without hypothesis tests. The only place I can think of where hypothesis tests offer something unique and useful is in the area of multiple degree of freedom joint hypothesis tests. Examples include ANOVA for comparing more than two groups, simultaneous tests combining main ef... | Why continue to teach and use hypothesis testing (when confidence intervals are available)? | I personally feel we would be better off without hypothesis tests. The only place I can think of where hypothesis tests offer something unique and useful is in the area of multiple degree of freedom | Why continue to teach and use hypothesis testing (when confidence intervals are available)?
I personally feel we would be better off without hypothesis tests. The only place I can think of where hypothesis tests offer something unique and useful is in the area of multiple degree of freedom joint hypothesis tests. Exa... | Why continue to teach and use hypothesis testing (when confidence intervals are available)?
I personally feel we would be better off without hypothesis tests. The only place I can think of where hypothesis tests offer something unique and useful is in the area of multiple degree of freedom |
4,325 | Why continue to teach and use hypothesis testing (when confidence intervals are available)? | I think it depends on which hypothesis testing you are talking about. The "classical" hypothesis testing (Neyman-Pearson) is said to be defective because it does not appropriately condition on what actually happened when you did the test. It instead is designed to work "regardless" of what you actually saw in the lon... | Why continue to teach and use hypothesis testing (when confidence intervals are available)? | I think it depends on which hypothesis testing you are talking about. The "classical" hypothesis testing (Neyman-Pearson) is said to be defective because it does not appropriately condition on what a | Why continue to teach and use hypothesis testing (when confidence intervals are available)?
I think it depends on which hypothesis testing you are talking about. The "classical" hypothesis testing (Neyman-Pearson) is said to be defective because it does not appropriately condition on what actually happened when you di... | Why continue to teach and use hypothesis testing (when confidence intervals are available)?
I think it depends on which hypothesis testing you are talking about. The "classical" hypothesis testing (Neyman-Pearson) is said to be defective because it does not appropriately condition on what a |
4,326 | Why continue to teach and use hypothesis testing (when confidence intervals are available)? | If I were a hardcore Frequentist I would remind you that confidence intervals are quite regularly just inverted hypothesis tests, i.e. when the 95% interval is simply another way of describing all the points that a test involving your data wouldn't reject at the .05 level. In these situations a preference for one over... | Why continue to teach and use hypothesis testing (when confidence intervals are available)? | If I were a hardcore Frequentist I would remind you that confidence intervals are quite regularly just inverted hypothesis tests, i.e. when the 95% interval is simply another way of describing all the | Why continue to teach and use hypothesis testing (when confidence intervals are available)?
If I were a hardcore Frequentist I would remind you that confidence intervals are quite regularly just inverted hypothesis tests, i.e. when the 95% interval is simply another way of describing all the points that a test involvin... | Why continue to teach and use hypothesis testing (when confidence intervals are available)?
If I were a hardcore Frequentist I would remind you that confidence intervals are quite regularly just inverted hypothesis tests, i.e. when the 95% interval is simply another way of describing all the |
4,327 | Why continue to teach and use hypothesis testing (when confidence intervals are available)? | In teaching Neyman Pearson hypothesis testing to early statistics students, I have often tried to locate it in its original setting: that of making decisions. Then the infrastructure of type 1 and type 2 errors all makes sense, as does the idea that you might accept the null hypothesis.
We have to make a decision, w... | Why continue to teach and use hypothesis testing (when confidence intervals are available)? | In teaching Neyman Pearson hypothesis testing to early statistics students, I have often tried to locate it in its original setting: that of making decisions. Then the infrastructure of type 1 and ty | Why continue to teach and use hypothesis testing (when confidence intervals are available)?
In teaching Neyman Pearson hypothesis testing to early statistics students, I have often tried to locate it in its original setting: that of making decisions. Then the infrastructure of type 1 and type 2 errors all makes sense,... | Why continue to teach and use hypothesis testing (when confidence intervals are available)?
In teaching Neyman Pearson hypothesis testing to early statistics students, I have often tried to locate it in its original setting: that of making decisions. Then the infrastructure of type 1 and ty |
4,328 | Why continue to teach and use hypothesis testing (when confidence intervals are available)? | Hypothesis testing is a useful way to frame a lot of questions: is the effect of a treatment zero or nonzero? The ability between statements such as these and a statistical model or procedure (including the construction of an interval estimator) is important for practitioners I think.
It also bears mentioning that a co... | Why continue to teach and use hypothesis testing (when confidence intervals are available)? | Hypothesis testing is a useful way to frame a lot of questions: is the effect of a treatment zero or nonzero? The ability between statements such as these and a statistical model or procedure (includi | Why continue to teach and use hypothesis testing (when confidence intervals are available)?
Hypothesis testing is a useful way to frame a lot of questions: is the effect of a treatment zero or nonzero? The ability between statements such as these and a statistical model or procedure (including the construction of an in... | Why continue to teach and use hypothesis testing (when confidence intervals are available)?
Hypothesis testing is a useful way to frame a lot of questions: is the effect of a treatment zero or nonzero? The ability between statements such as these and a statistical model or procedure (includi |
4,329 | Why continue to teach and use hypothesis testing (when confidence intervals are available)? | The reason is decision making. In most decision making you either do it or not. You may keep looking at intervals all day long, in the end there's a moment where you decide to do it or not.
Hypothesis testing fits nicely into this simple reality of YES/NO. | Why continue to teach and use hypothesis testing (when confidence intervals are available)? | The reason is decision making. In most decision making you either do it or not. You may keep looking at intervals all day long, in the end there's a moment where you decide to do it or not.
Hypothesi | Why continue to teach and use hypothesis testing (when confidence intervals are available)?
The reason is decision making. In most decision making you either do it or not. You may keep looking at intervals all day long, in the end there's a moment where you decide to do it or not.
Hypothesis testing fits nicely into t... | Why continue to teach and use hypothesis testing (when confidence intervals are available)?
The reason is decision making. In most decision making you either do it or not. You may keep looking at intervals all day long, in the end there's a moment where you decide to do it or not.
Hypothesi |
4,330 | What are some examples of anachronistic practices in statistics? | It's strongly arguable that the use of threshold significance levels such as $P = 0.05$ or $P = 0.01$ is a historical hangover from a period when most researchers depended on previously calculated tables of critical values. Now good software will give $P$-values directly. Indeed, good software lets you customise your a... | What are some examples of anachronistic practices in statistics? | It's strongly arguable that the use of threshold significance levels such as $P = 0.05$ or $P = 0.01$ is a historical hangover from a period when most researchers depended on previously calculated tab | What are some examples of anachronistic practices in statistics?
It's strongly arguable that the use of threshold significance levels such as $P = 0.05$ or $P = 0.01$ is a historical hangover from a period when most researchers depended on previously calculated tables of critical values. Now good software will give $P$... | What are some examples of anachronistic practices in statistics?
It's strongly arguable that the use of threshold significance levels such as $P = 0.05$ or $P = 0.01$ is a historical hangover from a period when most researchers depended on previously calculated tab |
4,331 | What are some examples of anachronistic practices in statistics? | One method that I think many visitors of this site will agree with me on is stepwise regression. It's still done all the time, but you don't have to search far for experts on this site saying deploring its use. A method like LASSO is much preferred. | What are some examples of anachronistic practices in statistics? | One method that I think many visitors of this site will agree with me on is stepwise regression. It's still done all the time, but you don't have to search far for experts on this site saying deplorin | What are some examples of anachronistic practices in statistics?
One method that I think many visitors of this site will agree with me on is stepwise regression. It's still done all the time, but you don't have to search far for experts on this site saying deploring its use. A method like LASSO is much preferred. | What are some examples of anachronistic practices in statistics?
One method that I think many visitors of this site will agree with me on is stepwise regression. It's still done all the time, but you don't have to search far for experts on this site saying deplorin |
4,332 | What are some examples of anachronistic practices in statistics? | My view is that at least in (applied) econometrics, it is more and more the norm to use the robust or empirical covariance matrix rather than the "anachronistic practice" of relying (asymptotically) on the correct specification of the covariance matrix. This is of course not without controversy: see some of the answers... | What are some examples of anachronistic practices in statistics? | My view is that at least in (applied) econometrics, it is more and more the norm to use the robust or empirical covariance matrix rather than the "anachronistic practice" of relying (asymptotically) o | What are some examples of anachronistic practices in statistics?
My view is that at least in (applied) econometrics, it is more and more the norm to use the robust or empirical covariance matrix rather than the "anachronistic practice" of relying (asymptotically) on the correct specification of the covariance matrix. T... | What are some examples of anachronistic practices in statistics?
My view is that at least in (applied) econometrics, it is more and more the norm to use the robust or empirical covariance matrix rather than the "anachronistic practice" of relying (asymptotically) o |
4,333 | What are some examples of anachronistic practices in statistics? | Most anachronistic practices are probably due to the way statistics is taught and the fact that analyses are run by huge numbers of people who have only taken a couple of basic classes. We often teach a set of standard statistical ideas and procedures because they form a logical sequence of increasing conceptual sophi... | What are some examples of anachronistic practices in statistics? | Most anachronistic practices are probably due to the way statistics is taught and the fact that analyses are run by huge numbers of people who have only taken a couple of basic classes. We often teac | What are some examples of anachronistic practices in statistics?
Most anachronistic practices are probably due to the way statistics is taught and the fact that analyses are run by huge numbers of people who have only taken a couple of basic classes. We often teach a set of standard statistical ideas and procedures be... | What are some examples of anachronistic practices in statistics?
Most anachronistic practices are probably due to the way statistics is taught and the fact that analyses are run by huge numbers of people who have only taken a couple of basic classes. We often teac |
4,334 | What are some examples of anachronistic practices in statistics? | A method that is unnecessarily used all the time is the Bonferroni correction to p-values. While multiple comparisons is as big an issue as it ever was, the Bonferroni correction is essentially obsolete for p-values: for any situation in which the Bonferroni correction is valid, so is the Holm-Bonferroni, which will ha... | What are some examples of anachronistic practices in statistics? | A method that is unnecessarily used all the time is the Bonferroni correction to p-values. While multiple comparisons is as big an issue as it ever was, the Bonferroni correction is essentially obsole | What are some examples of anachronistic practices in statistics?
A method that is unnecessarily used all the time is the Bonferroni correction to p-values. While multiple comparisons is as big an issue as it ever was, the Bonferroni correction is essentially obsolete for p-values: for any situation in which the Bonferr... | What are some examples of anachronistic practices in statistics?
A method that is unnecessarily used all the time is the Bonferroni correction to p-values. While multiple comparisons is as big an issue as it ever was, the Bonferroni correction is essentially obsole |
4,335 | What are some examples of anachronistic practices in statistics? | Paying licensing fees for high-quality statistical software systems. #R | What are some examples of anachronistic practices in statistics? | Paying licensing fees for high-quality statistical software systems. #R | What are some examples of anachronistic practices in statistics?
Paying licensing fees for high-quality statistical software systems. #R | What are some examples of anachronistic practices in statistics?
Paying licensing fees for high-quality statistical software systems. #R |
4,336 | What are some examples of anachronistic practices in statistics? | A very interesting example are unit root tests in econometrics. While there are plenty of choices available to test against or for a unit root in the lag polynomial of a time series (e.g., the (Augmented) Dickey Fuller Test or the KPSS test), the problem can be circumvented completely when one uses Bayesian analysis. S... | What are some examples of anachronistic practices in statistics? | A very interesting example are unit root tests in econometrics. While there are plenty of choices available to test against or for a unit root in the lag polynomial of a time series (e.g., the (Augmen | What are some examples of anachronistic practices in statistics?
A very interesting example are unit root tests in econometrics. While there are plenty of choices available to test against or for a unit root in the lag polynomial of a time series (e.g., the (Augmented) Dickey Fuller Test or the KPSS test), the problem ... | What are some examples of anachronistic practices in statistics?
A very interesting example are unit root tests in econometrics. While there are plenty of choices available to test against or for a unit root in the lag polynomial of a time series (e.g., the (Augmen |
4,337 | What are some examples of anachronistic practices in statistics? | Teaching/conducting two-tailed tests for difference without simultaneously testing for equivalence in the frequentist realm of hypothesis testing is a deep commitment to confirmation bias.
There's some nuance, in that an appropriate power analysis with thoughtful definition of effect size can guard against this and pro... | What are some examples of anachronistic practices in statistics? | Teaching/conducting two-tailed tests for difference without simultaneously testing for equivalence in the frequentist realm of hypothesis testing is a deep commitment to confirmation bias.
There's som | What are some examples of anachronistic practices in statistics?
Teaching/conducting two-tailed tests for difference without simultaneously testing for equivalence in the frequentist realm of hypothesis testing is a deep commitment to confirmation bias.
There's some nuance, in that an appropriate power analysis with th... | What are some examples of anachronistic practices in statistics?
Teaching/conducting two-tailed tests for difference without simultaneously testing for equivalence in the frequentist realm of hypothesis testing is a deep commitment to confirmation bias.
There's som |
4,338 | What are some examples of anachronistic practices in statistics? | Using a Negative Binomial model rather than a (robust) Poisson model to identify a parameter of interest in a count variable, only because there is over-dispersion ?
See as a reference: https://blog.stata.com/2011/08/22/use-poisson-rather-than-regress-tell-a-friend/
The proof that Poisson is more robust in the case of ... | What are some examples of anachronistic practices in statistics? | Using a Negative Binomial model rather than a (robust) Poisson model to identify a parameter of interest in a count variable, only because there is over-dispersion ?
See as a reference: https://blog.s | What are some examples of anachronistic practices in statistics?
Using a Negative Binomial model rather than a (robust) Poisson model to identify a parameter of interest in a count variable, only because there is over-dispersion ?
See as a reference: https://blog.stata.com/2011/08/22/use-poisson-rather-than-regress-tel... | What are some examples of anachronistic practices in statistics?
Using a Negative Binomial model rather than a (robust) Poisson model to identify a parameter of interest in a count variable, only because there is over-dispersion ?
See as a reference: https://blog.s |
4,339 | What are some examples of anachronistic practices in statistics? | Here are a few anachronisms:
The neoplatonic assumption that there is a single, "true" population out there in the theoretical ether that is eternal, fixed and unmoving against which our imperfect samples can be evaluated does little to advance learning and knowledge.
The reductionism inherent in mandates such as Occa... | What are some examples of anachronistic practices in statistics? | Here are a few anachronisms:
The neoplatonic assumption that there is a single, "true" population out there in the theoretical ether that is eternal, fixed and unmoving against which our imperfect sa | What are some examples of anachronistic practices in statistics?
Here are a few anachronisms:
The neoplatonic assumption that there is a single, "true" population out there in the theoretical ether that is eternal, fixed and unmoving against which our imperfect samples can be evaluated does little to advance learning ... | What are some examples of anachronistic practices in statistics?
Here are a few anachronisms:
The neoplatonic assumption that there is a single, "true" population out there in the theoretical ether that is eternal, fixed and unmoving against which our imperfect sa |
4,340 | Are we exaggerating importance of model assumption and evaluation in an era when analyses are often carried out by laymen | I am trained as a statistician not as a biologist or medical doctor. But I do quite a bit of medical research (working with biologists and medical doctors), as part of my research I have learned quite a bit about treatment of several different diseases. Does this mean that if a friend asks me about a disease that I h... | Are we exaggerating importance of model assumption and evaluation in an era when analyses are often | I am trained as a statistician not as a biologist or medical doctor. But I do quite a bit of medical research (working with biologists and medical doctors), as part of my research I have learned quit | Are we exaggerating importance of model assumption and evaluation in an era when analyses are often carried out by laymen
I am trained as a statistician not as a biologist or medical doctor. But I do quite a bit of medical research (working with biologists and medical doctors), as part of my research I have learned qu... | Are we exaggerating importance of model assumption and evaluation in an era when analyses are often
I am trained as a statistician not as a biologist or medical doctor. But I do quite a bit of medical research (working with biologists and medical doctors), as part of my research I have learned quit |
4,341 | Are we exaggerating importance of model assumption and evaluation in an era when analyses are often carried out by laymen | Well, yes, assumptions matter -- if they didn't matter at all, we wouldn't need to make them, would we?
The question is how much they matter -- this varies across procedures and assumptions and what you want to claim about your results (and also how tolerant your audience is of approximation -- even inaccuracy -- in su... | Are we exaggerating importance of model assumption and evaluation in an era when analyses are often | Well, yes, assumptions matter -- if they didn't matter at all, we wouldn't need to make them, would we?
The question is how much they matter -- this varies across procedures and assumptions and what y | Are we exaggerating importance of model assumption and evaluation in an era when analyses are often carried out by laymen
Well, yes, assumptions matter -- if they didn't matter at all, we wouldn't need to make them, would we?
The question is how much they matter -- this varies across procedures and assumptions and what... | Are we exaggerating importance of model assumption and evaluation in an era when analyses are often
Well, yes, assumptions matter -- if they didn't matter at all, we wouldn't need to make them, would we?
The question is how much they matter -- this varies across procedures and assumptions and what y |
4,342 | Are we exaggerating importance of model assumption and evaluation in an era when analyses are often carried out by laymen | While Glen_b gave a great answer, I would like to add a couple of cents to that.
One consideration is whether you really want to get the scientific truth, which would require polishing your results and figuring out all the details of whether your approach is defensible, vs. publishing in the "ah well, nobody checks the... | Are we exaggerating importance of model assumption and evaluation in an era when analyses are often | While Glen_b gave a great answer, I would like to add a couple of cents to that.
One consideration is whether you really want to get the scientific truth, which would require polishing your results an | Are we exaggerating importance of model assumption and evaluation in an era when analyses are often carried out by laymen
While Glen_b gave a great answer, I would like to add a couple of cents to that.
One consideration is whether you really want to get the scientific truth, which would require polishing your results ... | Are we exaggerating importance of model assumption and evaluation in an era when analyses are often
While Glen_b gave a great answer, I would like to add a couple of cents to that.
One consideration is whether you really want to get the scientific truth, which would require polishing your results an |
4,343 | Are we exaggerating importance of model assumption and evaluation in an era when analyses are often carried out by laymen | The nature of violations of assumptions can be an important clue for future research. For example, a violation of the proportional-hazards assumption in Cox survival analysis might be due to a variable with a large effect on short-term survival but little effect in the longer term. That's the type of unexpected but pot... | Are we exaggerating importance of model assumption and evaluation in an era when analyses are often | The nature of violations of assumptions can be an important clue for future research. For example, a violation of the proportional-hazards assumption in Cox survival analysis might be due to a variabl | Are we exaggerating importance of model assumption and evaluation in an era when analyses are often carried out by laymen
The nature of violations of assumptions can be an important clue for future research. For example, a violation of the proportional-hazards assumption in Cox survival analysis might be due to a varia... | Are we exaggerating importance of model assumption and evaluation in an era when analyses are often
The nature of violations of assumptions can be an important clue for future research. For example, a violation of the proportional-hazards assumption in Cox survival analysis might be due to a variabl |
4,344 | Are we exaggerating importance of model assumption and evaluation in an era when analyses are often carried out by laymen | I'll answer from an intermediate perspective. I'm not a statistician, I'm chemist. However, I've spent the last 10 years specializing in chemometrics = statistical data analysis for chemistry-related data.
I simply believe that researchers are not doing their statistics well enough.
That is probably the case.
Shor... | Are we exaggerating importance of model assumption and evaluation in an era when analyses are often | I'll answer from an intermediate perspective. I'm not a statistician, I'm chemist. However, I've spent the last 10 years specializing in chemometrics = statistical data analysis for chemistry-related | Are we exaggerating importance of model assumption and evaluation in an era when analyses are often carried out by laymen
I'll answer from an intermediate perspective. I'm not a statistician, I'm chemist. However, I've spent the last 10 years specializing in chemometrics = statistical data analysis for chemistry-relate... | Are we exaggerating importance of model assumption and evaluation in an era when analyses are often
I'll answer from an intermediate perspective. I'm not a statistician, I'm chemist. However, I've spent the last 10 years specializing in chemometrics = statistical data analysis for chemistry-related |
4,345 | Are we exaggerating importance of model assumption and evaluation in an era when analyses are often carried out by laymen | Given that CV is populated by statisticians and people who are curious, if not competent, about statistics, I am not surprised about all the answers emphasizing the need to understand the assumptions. I also agree with these answers in principle.
However, when taking account the pressure to publish and the low standard... | Are we exaggerating importance of model assumption and evaluation in an era when analyses are often | Given that CV is populated by statisticians and people who are curious, if not competent, about statistics, I am not surprised about all the answers emphasizing the need to understand the assumptions. | Are we exaggerating importance of model assumption and evaluation in an era when analyses are often carried out by laymen
Given that CV is populated by statisticians and people who are curious, if not competent, about statistics, I am not surprised about all the answers emphasizing the need to understand the assumption... | Are we exaggerating importance of model assumption and evaluation in an era when analyses are often
Given that CV is populated by statisticians and people who are curious, if not competent, about statistics, I am not surprised about all the answers emphasizing the need to understand the assumptions. |
4,346 | Are we exaggerating importance of model assumption and evaluation in an era when analyses are often carried out by laymen | The short answer is "no." Statistical methods were developed under sets of assumptions that should be met for the results to be valid. It stands to reason, then, that if the assumptions were not met, the results may not be valid. Of course, some estimates may still be robust despite violations of model assumptions. ... | Are we exaggerating importance of model assumption and evaluation in an era when analyses are often | The short answer is "no." Statistical methods were developed under sets of assumptions that should be met for the results to be valid. It stands to reason, then, that if the assumptions were not met, | Are we exaggerating importance of model assumption and evaluation in an era when analyses are often carried out by laymen
The short answer is "no." Statistical methods were developed under sets of assumptions that should be met for the results to be valid. It stands to reason, then, that if the assumptions were not me... | Are we exaggerating importance of model assumption and evaluation in an era when analyses are often
The short answer is "no." Statistical methods were developed under sets of assumptions that should be met for the results to be valid. It stands to reason, then, that if the assumptions were not met, |
4,347 | Are we exaggerating importance of model assumption and evaluation in an era when analyses are often carried out by laymen | If you need very advanced statistics it's most likely because your data is a mess, which is the case with most social sciences, not to mention psychology. In those fields where you have good data you need very little statistics. Physics is a very good example.
Consider this quote from Galileo on his famous gravitation... | Are we exaggerating importance of model assumption and evaluation in an era when analyses are often | If you need very advanced statistics it's most likely because your data is a mess, which is the case with most social sciences, not to mention psychology. In those fields where you have good data you | Are we exaggerating importance of model assumption and evaluation in an era when analyses are often carried out by laymen
If you need very advanced statistics it's most likely because your data is a mess, which is the case with most social sciences, not to mention psychology. In those fields where you have good data yo... | Are we exaggerating importance of model assumption and evaluation in an era when analyses are often
If you need very advanced statistics it's most likely because your data is a mess, which is the case with most social sciences, not to mention psychology. In those fields where you have good data you |
4,348 | Are we exaggerating importance of model assumption and evaluation in an era when analyses are often carried out by laymen | This question seems to be a case of professional integrity.
The problem seems to be that either:
(a) there isn't enough critical assessment of statistical analysis by lay persons or
(b) a case of common knowledge is insufficient to identify statistical error (like a Type 2 error)?
I know enough about my area of experti... | Are we exaggerating importance of model assumption and evaluation in an era when analyses are often | This question seems to be a case of professional integrity.
The problem seems to be that either:
(a) there isn't enough critical assessment of statistical analysis by lay persons or
(b) a case of comm | Are we exaggerating importance of model assumption and evaluation in an era when analyses are often carried out by laymen
This question seems to be a case of professional integrity.
The problem seems to be that either:
(a) there isn't enough critical assessment of statistical analysis by lay persons or
(b) a case of co... | Are we exaggerating importance of model assumption and evaluation in an era when analyses are often
This question seems to be a case of professional integrity.
The problem seems to be that either:
(a) there isn't enough critical assessment of statistical analysis by lay persons or
(b) a case of comm |
4,349 | Which has the heavier tail, lognormal or gamma? | The (right) tail of a distribution describes its behavior at large values. The correct object to study is not its density--which in many practical cases does not exist--but rather its distribution function $F$. More specifically, because $F$ must rise asymptotically to $1$ for large arguments $x$ (by the Law of Total... | Which has the heavier tail, lognormal or gamma? | The (right) tail of a distribution describes its behavior at large values. The correct object to study is not its density--which in many practical cases does not exist--but rather its distribution fu | Which has the heavier tail, lognormal or gamma?
The (right) tail of a distribution describes its behavior at large values. The correct object to study is not its density--which in many practical cases does not exist--but rather its distribution function $F$. More specifically, because $F$ must rise asymptotically to ... | Which has the heavier tail, lognormal or gamma?
The (right) tail of a distribution describes its behavior at large values. The correct object to study is not its density--which in many practical cases does not exist--but rather its distribution fu |
4,350 | Which has the heavier tail, lognormal or gamma? | The gamma and the lognormal are both right skew, constant-coefficient-of-variation distributions on $(0,\infty)$, and they're often the basis of "competing" models for particular kinds of phenomena.
There are various ways to define the heaviness of a tail, but in this case I think all the usual ones show that the logno... | Which has the heavier tail, lognormal or gamma? | The gamma and the lognormal are both right skew, constant-coefficient-of-variation distributions on $(0,\infty)$, and they're often the basis of "competing" models for particular kinds of phenomena.
T | Which has the heavier tail, lognormal or gamma?
The gamma and the lognormal are both right skew, constant-coefficient-of-variation distributions on $(0,\infty)$, and they're often the basis of "competing" models for particular kinds of phenomena.
There are various ways to define the heaviness of a tail, but in this cas... | Which has the heavier tail, lognormal or gamma?
The gamma and the lognormal are both right skew, constant-coefficient-of-variation distributions on $(0,\infty)$, and they're often the basis of "competing" models for particular kinds of phenomena.
T |
4,351 | Which has the heavier tail, lognormal or gamma? | Although kurtosis is a related to the heaviness of tails, it would contribute more to the notion of fat tailed distributions, and relatively less to tail heaviness itself, as the following example shows. Herein, I now regurgitate what I have learned in the posts above and below, which are really excellent comments. Fir... | Which has the heavier tail, lognormal or gamma? | Although kurtosis is a related to the heaviness of tails, it would contribute more to the notion of fat tailed distributions, and relatively less to tail heaviness itself, as the following example sho | Which has the heavier tail, lognormal or gamma?
Although kurtosis is a related to the heaviness of tails, it would contribute more to the notion of fat tailed distributions, and relatively less to tail heaviness itself, as the following example shows. Herein, I now regurgitate what I have learned in the posts above and... | Which has the heavier tail, lognormal or gamma?
Although kurtosis is a related to the heaviness of tails, it would contribute more to the notion of fat tailed distributions, and relatively less to tail heaviness itself, as the following example sho |
4,352 | Software for drawing bayesian networks (graphical models) | I currently have a similar problem (drawing multiple path diagrams for my dissertation), and so I was examining many of the options listed here already to draw similar diagrams. Many of the listed resources for drawing such vector graphics (such as in microsoft office or google drawings) can produce really nice path di... | Software for drawing bayesian networks (graphical models) | I currently have a similar problem (drawing multiple path diagrams for my dissertation), and so I was examining many of the options listed here already to draw similar diagrams. Many of the listed res | Software for drawing bayesian networks (graphical models)
I currently have a similar problem (drawing multiple path diagrams for my dissertation), and so I was examining many of the options listed here already to draw similar diagrams. Many of the listed resources for drawing such vector graphics (such as in microsoft ... | Software for drawing bayesian networks (graphical models)
I currently have a similar problem (drawing multiple path diagrams for my dissertation), and so I was examining many of the options listed here already to draw similar diagrams. Many of the listed res |
4,353 | Software for drawing bayesian networks (graphical models) | Laura Dietz has written a very nice library for tikz that enables drawing of Bayesian Networks in latex without needing to actually use tikz directly.
To demonstrate this package, see the following example for this question:
\documentclass[11pt]{report}
\usepackage{tikz}
\usetikzlibrary{bayesnet}
\begin{document}
\begi... | Software for drawing bayesian networks (graphical models) | Laura Dietz has written a very nice library for tikz that enables drawing of Bayesian Networks in latex without needing to actually use tikz directly.
To demonstrate this package, see the following ex | Software for drawing bayesian networks (graphical models)
Laura Dietz has written a very nice library for tikz that enables drawing of Bayesian Networks in latex without needing to actually use tikz directly.
To demonstrate this package, see the following example for this question:
\documentclass[11pt]{report}
\usepack... | Software for drawing bayesian networks (graphical models)
Laura Dietz has written a very nice library for tikz that enables drawing of Bayesian Networks in latex without needing to actually use tikz directly.
To demonstrate this package, see the following ex |
4,354 | Software for drawing bayesian networks (graphical models) | You can't beat http://daft-pgm.org/
Daft is a Python package that uses matplotlib to render pixel-perfect probabilistic graphical models for publication in a journal or on the internet. With a short Python script and an intuitive model-building syntax you can design directed (Bayesian Networks, directed acyclic graphs... | Software for drawing bayesian networks (graphical models) | You can't beat http://daft-pgm.org/
Daft is a Python package that uses matplotlib to render pixel-perfect probabilistic graphical models for publication in a journal or on the internet. With a short | Software for drawing bayesian networks (graphical models)
You can't beat http://daft-pgm.org/
Daft is a Python package that uses matplotlib to render pixel-perfect probabilistic graphical models for publication in a journal or on the internet. With a short Python script and an intuitive model-building syntax you can d... | Software for drawing bayesian networks (graphical models)
You can't beat http://daft-pgm.org/
Daft is a Python package that uses matplotlib to render pixel-perfect probabilistic graphical models for publication in a journal or on the internet. With a short |
4,355 | Software for drawing bayesian networks (graphical models) | You could try GraphViz.
This allows you to specify the graph in a text-file and it will be drawn automatically (avoiding overlapping arrows and so on). Go here (pdf) for a minimal example and a manual. | Software for drawing bayesian networks (graphical models) | You could try GraphViz.
This allows you to specify the graph in a text-file and it will be drawn automatically (avoiding overlapping arrows and so on). Go here (pdf) for a minimal example and a manual | Software for drawing bayesian networks (graphical models)
You could try GraphViz.
This allows you to specify the graph in a text-file and it will be drawn automatically (avoiding overlapping arrows and so on). Go here (pdf) for a minimal example and a manual. | Software for drawing bayesian networks (graphical models)
You could try GraphViz.
This allows you to specify the graph in a text-file and it will be drawn automatically (avoiding overlapping arrows and so on). Go here (pdf) for a minimal example and a manual |
4,356 | Software for drawing bayesian networks (graphical models) | Inkscape is essentially a free version of Adobe Illustrator, and is a very strong program for doing vector graphics, like the picture you posted. It also plays rather nicely with most statistical packages for doing final edits/annotations/etc. to graphs - R, SAS, etc. can output a graph as a PDF or other vector format ... | Software for drawing bayesian networks (graphical models) | Inkscape is essentially a free version of Adobe Illustrator, and is a very strong program for doing vector graphics, like the picture you posted. It also plays rather nicely with most statistical pack | Software for drawing bayesian networks (graphical models)
Inkscape is essentially a free version of Adobe Illustrator, and is a very strong program for doing vector graphics, like the picture you posted. It also plays rather nicely with most statistical packages for doing final edits/annotations/etc. to graphs - R, SAS... | Software for drawing bayesian networks (graphical models)
Inkscape is essentially a free version of Adobe Illustrator, and is a very strong program for doing vector graphics, like the picture you posted. It also plays rather nicely with most statistical pack |
4,357 | Software for drawing bayesian networks (graphical models) | If you have a particular interest in using LaTeX, the LaTeXDraw program has some nice functionality for creating flow charts with embedded latex code.
It imports / exports PSTricks code and SVG, and can also export svg, pdf, eps, jpg, png, etc. It runs in Linux, Mac OS X, and Windows. | Software for drawing bayesian networks (graphical models) | If you have a particular interest in using LaTeX, the LaTeXDraw program has some nice functionality for creating flow charts with embedded latex code.
It imports / exports PSTricks code and SVG, and | Software for drawing bayesian networks (graphical models)
If you have a particular interest in using LaTeX, the LaTeXDraw program has some nice functionality for creating flow charts with embedded latex code.
It imports / exports PSTricks code and SVG, and can also export svg, pdf, eps, jpg, png, etc. It runs in Linu... | Software for drawing bayesian networks (graphical models)
If you have a particular interest in using LaTeX, the LaTeXDraw program has some nice functionality for creating flow charts with embedded latex code.
It imports / exports PSTricks code and SVG, and |
4,358 | Software for drawing bayesian networks (graphical models) | Dia is a free open source program for drawing diagrams. I find it useful and it's not too difficult to get started. | Software for drawing bayesian networks (graphical models) | Dia is a free open source program for drawing diagrams. I find it useful and it's not too difficult to get started. | Software for drawing bayesian networks (graphical models)
Dia is a free open source program for drawing diagrams. I find it useful and it's not too difficult to get started. | Software for drawing bayesian networks (graphical models)
Dia is a free open source program for drawing diagrams. I find it useful and it's not too difficult to get started. |
4,359 | Software for drawing bayesian networks (graphical models) | I have found Diagrammix to be a very flexible package, available for Mac OS X. It is a well rounded vector graphics package and does a good job at graphical models. It is fairly inexpensive and has some good add-ons that have helped improve the shapes and directions of edges. | Software for drawing bayesian networks (graphical models) | I have found Diagrammix to be a very flexible package, available for Mac OS X. It is a well rounded vector graphics package and does a good job at graphical models. It is fairly inexpensive and has | Software for drawing bayesian networks (graphical models)
I have found Diagrammix to be a very flexible package, available for Mac OS X. It is a well rounded vector graphics package and does a good job at graphical models. It is fairly inexpensive and has some good add-ons that have helped improve the shapes and dire... | Software for drawing bayesian networks (graphical models)
I have found Diagrammix to be a very flexible package, available for Mac OS X. It is a well rounded vector graphics package and does a good job at graphical models. It is fairly inexpensive and has |
4,360 | Software for drawing bayesian networks (graphical models) | You could try Google Docs Draw. It looks like it will do what you want for free, right in your browser. | Software for drawing bayesian networks (graphical models) | You could try Google Docs Draw. It looks like it will do what you want for free, right in your browser. | Software for drawing bayesian networks (graphical models)
You could try Google Docs Draw. It looks like it will do what you want for free, right in your browser. | Software for drawing bayesian networks (graphical models)
You could try Google Docs Draw. It looks like it will do what you want for free, right in your browser. |
4,361 | Software for drawing bayesian networks (graphical models) | You can go for PlantUML. It is open source and quite flexible. | Software for drawing bayesian networks (graphical models) | You can go for PlantUML. It is open source and quite flexible. | Software for drawing bayesian networks (graphical models)
You can go for PlantUML. It is open source and quite flexible. | Software for drawing bayesian networks (graphical models)
You can go for PlantUML. It is open source and quite flexible. |
4,362 | Software for drawing bayesian networks (graphical models) | You can also use the Lucidchart webapp.
I've used it in the past for drawing graphs and it's free. | Software for drawing bayesian networks (graphical models) | You can also use the Lucidchart webapp.
I've used it in the past for drawing graphs and it's free. | Software for drawing bayesian networks (graphical models)
You can also use the Lucidchart webapp.
I've used it in the past for drawing graphs and it's free. | Software for drawing bayesian networks (graphical models)
You can also use the Lucidchart webapp.
I've used it in the past for drawing graphs and it's free. |
4,363 | Software for drawing bayesian networks (graphical models) | SCAVIS has a Bayesian network. Try to google "scavis baysian network".
The same program can draw different diagrams using Python (or Java) syntax. | Software for drawing bayesian networks (graphical models) | SCAVIS has a Bayesian network. Try to google "scavis baysian network".
The same program can draw different diagrams using Python (or Java) syntax. | Software for drawing bayesian networks (graphical models)
SCAVIS has a Bayesian network. Try to google "scavis baysian network".
The same program can draw different diagrams using Python (or Java) syntax. | Software for drawing bayesian networks (graphical models)
SCAVIS has a Bayesian network. Try to google "scavis baysian network".
The same program can draw different diagrams using Python (or Java) syntax. |
4,364 | Software for drawing bayesian networks (graphical models) | you can use draw.io and use one or their many templates to create these icons. It helps you create SVGs or any other format. and does not require you to install anything on your system. | Software for drawing bayesian networks (graphical models) | you can use draw.io and use one or their many templates to create these icons. It helps you create SVGs or any other format. and does not require you to install anything on your system. | Software for drawing bayesian networks (graphical models)
you can use draw.io and use one or their many templates to create these icons. It helps you create SVGs or any other format. and does not require you to install anything on your system. | Software for drawing bayesian networks (graphical models)
you can use draw.io and use one or their many templates to create these icons. It helps you create SVGs or any other format. and does not require you to install anything on your system. |
4,365 | Is it unusual for the MEAN to outperform ARIMA? | I'm a practitioner, both producer and user of forecasting and NOT a trained statistician. Below I share some of my thoughts on why your mean forecast turned out better than ARIMA by referring to research article that rely on empirical evidence. One book that time and time again I go back to refer is the Principles of ... | Is it unusual for the MEAN to outperform ARIMA? | I'm a practitioner, both producer and user of forecasting and NOT a trained statistician. Below I share some of my thoughts on why your mean forecast turned out better than ARIMA by referring to resea | Is it unusual for the MEAN to outperform ARIMA?
I'm a practitioner, both producer and user of forecasting and NOT a trained statistician. Below I share some of my thoughts on why your mean forecast turned out better than ARIMA by referring to research article that rely on empirical evidence. One book that time and tim... | Is it unusual for the MEAN to outperform ARIMA?
I'm a practitioner, both producer and user of forecasting and NOT a trained statistician. Below I share some of my thoughts on why your mean forecast turned out better than ARIMA by referring to resea |
4,366 | Is it unusual for the MEAN to outperform ARIMA? | This is not at all surprising. In forecasting, you very often find that extremely simple methods, like
the overall mean
the naive random walk (i.e., the last observation used as a forecast)
a seasonal random walk (i.e., the observation from one year back)
Single Exponential Smoothing
outperform more complex methods. ... | Is it unusual for the MEAN to outperform ARIMA? | This is not at all surprising. In forecasting, you very often find that extremely simple methods, like
the overall mean
the naive random walk (i.e., the last observation used as a forecast)
a seasona | Is it unusual for the MEAN to outperform ARIMA?
This is not at all surprising. In forecasting, you very often find that extremely simple methods, like
the overall mean
the naive random walk (i.e., the last observation used as a forecast)
a seasonal random walk (i.e., the observation from one year back)
Single Exponent... | Is it unusual for the MEAN to outperform ARIMA?
This is not at all surprising. In forecasting, you very often find that extremely simple methods, like
the overall mean
the naive random walk (i.e., the last observation used as a forecast)
a seasona |
4,367 | What is the difference between GARCH and ARMA? | You are conflating the features of a process with its representation. Consider the (return) process $(Y_t)_{t=0}^\infty$.
An ARMA(p,q) model specifies the conditional mean of the process as
$$
\begin{align}
\mathbb{E}(Y_t \mid \mathcal{I}_t) &= \alpha_0 + \sum_{j=1}^p \alpha_j Y_{t-j}+ \sum_{k=1}^q \beta_k\epsilon_{... | What is the difference between GARCH and ARMA? | You are conflating the features of a process with its representation. Consider the (return) process $(Y_t)_{t=0}^\infty$.
An ARMA(p,q) model specifies the conditional mean of the process as
$$
\beg | What is the difference between GARCH and ARMA?
You are conflating the features of a process with its representation. Consider the (return) process $(Y_t)_{t=0}^\infty$.
An ARMA(p,q) model specifies the conditional mean of the process as
$$
\begin{align}
\mathbb{E}(Y_t \mid \mathcal{I}_t) &= \alpha_0 + \sum_{j=1}^p \... | What is the difference between GARCH and ARMA?
You are conflating the features of a process with its representation. Consider the (return) process $(Y_t)_{t=0}^\infty$.
An ARMA(p,q) model specifies the conditional mean of the process as
$$
\beg |
4,368 | What is the difference between GARCH and ARMA? | Edit: I realized the answer was lacking and have thus provided a more precise answer (see below -- or maybe above). I have edited this one for factual mistakes and am leaving it for the record.
Different focus parameters:
ARMA is a model for the realizations of a stochastic process imposing a specific structure of th... | What is the difference between GARCH and ARMA? | Edit: I realized the answer was lacking and have thus provided a more precise answer (see below -- or maybe above). I have edited this one for factual mistakes and am leaving it for the record.
Diffe | What is the difference between GARCH and ARMA?
Edit: I realized the answer was lacking and have thus provided a more precise answer (see below -- or maybe above). I have edited this one for factual mistakes and am leaving it for the record.
Different focus parameters:
ARMA is a model for the realizations of a stochas... | What is the difference between GARCH and ARMA?
Edit: I realized the answer was lacking and have thus provided a more precise answer (see below -- or maybe above). I have edited this one for factual mistakes and am leaving it for the record.
Diffe |
4,369 | What is the difference between GARCH and ARMA? | ARMA
Consider $y_t$ that follows an ARMA($p,q$) process. Suppose for simplicity it has zero mean and constant variance. Conditionally on information $I_{t-1}$, $y_t$ can be partitioned into a known (predetermined) part $\mu_t$ (which is the conditional mean of $y_t$ given $I_{t-1}$) and a random part $u_t$:
\begin{alig... | What is the difference between GARCH and ARMA? | ARMA
Consider $y_t$ that follows an ARMA($p,q$) process. Suppose for simplicity it has zero mean and constant variance. Conditionally on information $I_{t-1}$, $y_t$ can be partitioned into a known (p | What is the difference between GARCH and ARMA?
ARMA
Consider $y_t$ that follows an ARMA($p,q$) process. Suppose for simplicity it has zero mean and constant variance. Conditionally on information $I_{t-1}$, $y_t$ can be partitioned into a known (predetermined) part $\mu_t$ (which is the conditional mean of $y_t$ given ... | What is the difference between GARCH and ARMA?
ARMA
Consider $y_t$ that follows an ARMA($p,q$) process. Suppose for simplicity it has zero mean and constant variance. Conditionally on information $I_{t-1}$, $y_t$ can be partitioned into a known (p |
4,370 | What is the difference between GARCH and ARMA? | The ARMA and GARCH processes are very similar in their presentation. The dividing line between the two is very thin since we get GARCH when an ARMA process is assumed for the error variance. | What is the difference between GARCH and ARMA? | The ARMA and GARCH processes are very similar in their presentation. The dividing line between the two is very thin since we get GARCH when an ARMA process is assumed for the error variance. | What is the difference between GARCH and ARMA?
The ARMA and GARCH processes are very similar in their presentation. The dividing line between the two is very thin since we get GARCH when an ARMA process is assumed for the error variance. | What is the difference between GARCH and ARMA?
The ARMA and GARCH processes are very similar in their presentation. The dividing line between the two is very thin since we get GARCH when an ARMA process is assumed for the error variance. |
4,371 | What is the difference between GARCH and ARMA? | the difference is in stochastic part or lack of it.
Notice the most recent time index of the stochastic part in your formulation of ARMA:
$$X_t=\varepsilon_t+\dots$$
Compare it to GARCH:
$$\sigma^2_t=r^2_{t-1}+\dots$$
You can immediately see that in ARMA at future time $t$ the disturbance $\varepsilon_{t}$ is not yet o... | What is the difference between GARCH and ARMA? | the difference is in stochastic part or lack of it.
Notice the most recent time index of the stochastic part in your formulation of ARMA:
$$X_t=\varepsilon_t+\dots$$
Compare it to GARCH:
$$\sigma^2_t= | What is the difference between GARCH and ARMA?
the difference is in stochastic part or lack of it.
Notice the most recent time index of the stochastic part in your formulation of ARMA:
$$X_t=\varepsilon_t+\dots$$
Compare it to GARCH:
$$\sigma^2_t=r^2_{t-1}+\dots$$
You can immediately see that in ARMA at future time $t$... | What is the difference between GARCH and ARMA?
the difference is in stochastic part or lack of it.
Notice the most recent time index of the stochastic part in your formulation of ARMA:
$$X_t=\varepsilon_t+\dots$$
Compare it to GARCH:
$$\sigma^2_t= |
4,372 | Statistical inference when the sample "is" the population | There may be varying opinions on this, but I would treat the population data as a sample and assume a hypothetical population, then make inferences in the usual way. One way to think about this is that there is an underlying data generating process responsible for the collected data, the "population" distribution.
I... | Statistical inference when the sample "is" the population | There may be varying opinions on this, but I would treat the population data as a sample and assume a hypothetical population, then make inferences in the usual way. One way to think about this is th | Statistical inference when the sample "is" the population
There may be varying opinions on this, but I would treat the population data as a sample and assume a hypothetical population, then make inferences in the usual way. One way to think about this is that there is an underlying data generating process responsible ... | Statistical inference when the sample "is" the population
There may be varying opinions on this, but I would treat the population data as a sample and assume a hypothetical population, then make inferences in the usual way. One way to think about this is th |
4,373 | Statistical inference when the sample "is" the population | Actually, if you're really positive you have the whole population, there's even no need to go into statistics. Then you know exactly how big the difference is, and there is no reason whatsoever to test it any more. A classical mistake is using statistical significance as "relevant" significance. If you sampled the popu... | Statistical inference when the sample "is" the population | Actually, if you're really positive you have the whole population, there's even no need to go into statistics. Then you know exactly how big the difference is, and there is no reason whatsoever to tes | Statistical inference when the sample "is" the population
Actually, if you're really positive you have the whole population, there's even no need to go into statistics. Then you know exactly how big the difference is, and there is no reason whatsoever to test it any more. A classical mistake is using statistical signif... | Statistical inference when the sample "is" the population
Actually, if you're really positive you have the whole population, there's even no need to go into statistics. Then you know exactly how big the difference is, and there is no reason whatsoever to tes |
4,374 | Statistical inference when the sample "is" the population | Traditionally, statistical inference is taught in the context of probability samples and the nature of sampling error. This model is the basis for the test of significance. However, there are other ways to model systematic departures from chance and it turns out that our parametric (sampling based) tests tend to be g... | Statistical inference when the sample "is" the population | Traditionally, statistical inference is taught in the context of probability samples and the nature of sampling error. This model is the basis for the test of significance. However, there are other | Statistical inference when the sample "is" the population
Traditionally, statistical inference is taught in the context of probability samples and the nature of sampling error. This model is the basis for the test of significance. However, there are other ways to model systematic departures from chance and it turns o... | Statistical inference when the sample "is" the population
Traditionally, statistical inference is taught in the context of probability samples and the nature of sampling error. This model is the basis for the test of significance. However, there are other |
4,375 | Statistical inference when the sample "is" the population | Assume the results indicate that candidates differ along lines of gender. For example, the proportion of those who completed the tests are as follows: 40% female and 60% male. To suggest the obvious, 40% is different than 60%. Now what is important is to decide: 1) your population of interest; 2) how your observations ... | Statistical inference when the sample "is" the population | Assume the results indicate that candidates differ along lines of gender. For example, the proportion of those who completed the tests are as follows: 40% female and 60% male. To suggest the obvious, | Statistical inference when the sample "is" the population
Assume the results indicate that candidates differ along lines of gender. For example, the proportion of those who completed the tests are as follows: 40% female and 60% male. To suggest the obvious, 40% is different than 60%. Now what is important is to decide:... | Statistical inference when the sample "is" the population
Assume the results indicate that candidates differ along lines of gender. For example, the proportion of those who completed the tests are as follows: 40% female and 60% male. To suggest the obvious, |
4,376 | Statistical inference when the sample "is" the population | If you consider whatever it is that you are measuring to be a random process, then yes statistical tests are relevant. Take for example, flipping a coin 10 times to see if it is fair. You get 6 heads and 4 tails - what do you conclude? | Statistical inference when the sample "is" the population | If you consider whatever it is that you are measuring to be a random process, then yes statistical tests are relevant. Take for example, flipping a coin 10 times to see if it is fair. You get 6 heads | Statistical inference when the sample "is" the population
If you consider whatever it is that you are measuring to be a random process, then yes statistical tests are relevant. Take for example, flipping a coin 10 times to see if it is fair. You get 6 heads and 4 tails - what do you conclude? | Statistical inference when the sample "is" the population
If you consider whatever it is that you are measuring to be a random process, then yes statistical tests are relevant. Take for example, flipping a coin 10 times to see if it is fair. You get 6 heads |
4,377 | Random forest computing time in R | The overall complexity of RF is something like $\text{ntree}\cdot\text{mtry}\cdot(\text{# objects})\log( \text{# objects})$; if you want to speed your computations up, you can try the following:
Use randomForest instead of party, or, even better, ranger or Rborist (although both are not yet battle-tested).
Don't use f... | Random forest computing time in R | The overall complexity of RF is something like $\text{ntree}\cdot\text{mtry}\cdot(\text{# objects})\log( \text{# objects})$; if you want to speed your computations up, you can try the following:
Use | Random forest computing time in R
The overall complexity of RF is something like $\text{ntree}\cdot\text{mtry}\cdot(\text{# objects})\log( \text{# objects})$; if you want to speed your computations up, you can try the following:
Use randomForest instead of party, or, even better, ranger or Rborist (although both are n... | Random forest computing time in R
The overall complexity of RF is something like $\text{ntree}\cdot\text{mtry}\cdot(\text{# objects})\log( \text{# objects})$; if you want to speed your computations up, you can try the following:
Use |
4,378 | Random forest computing time in R | Because randomForest is a collection of independent carts trained upon a random subset of features and records it lends itself to parallelization. The combine() function in the randomForest package will stitch together independently trained forests. Here is a toy example. As @mpq 's answer states you should not use th... | Random forest computing time in R | Because randomForest is a collection of independent carts trained upon a random subset of features and records it lends itself to parallelization. The combine() function in the randomForest package wi | Random forest computing time in R
Because randomForest is a collection of independent carts trained upon a random subset of features and records it lends itself to parallelization. The combine() function in the randomForest package will stitch together independently trained forests. Here is a toy example. As @mpq 's an... | Random forest computing time in R
Because randomForest is a collection of independent carts trained upon a random subset of features and records it lends itself to parallelization. The combine() function in the randomForest package wi |
4,379 | Random forest computing time in R | I can't speak to the speed of specific algorithms in R but it should be obvious what is causing long computing time. For each tree at each branch CART is looking form the best binary split. So for each of the 34 features it most look at the splits given by each of the levels of the variables. Multiply the run time fo... | Random forest computing time in R | I can't speak to the speed of specific algorithms in R but it should be obvious what is causing long computing time. For each tree at each branch CART is looking form the best binary split. So for e | Random forest computing time in R
I can't speak to the speed of specific algorithms in R but it should be obvious what is causing long computing time. For each tree at each branch CART is looking form the best binary split. So for each of the 34 features it most look at the splits given by each of the levels of the v... | Random forest computing time in R
I can't speak to the speed of specific algorithms in R but it should be obvious what is causing long computing time. For each tree at each branch CART is looking form the best binary split. So for e |
4,380 | Random forest computing time in R | I would suggest a couple of links:
1) Shrink number of levels of a factor variable
is a link to a question on stackoverflow to deal with a similar issue while using the randomForest package. Specifically it deals with using only the most frequently occurring levels and assigning a new level to all other, less freque... | Random forest computing time in R | I would suggest a couple of links:
1) Shrink number of levels of a factor variable
is a link to a question on stackoverflow to deal with a similar issue while using the randomForest package. Specif | Random forest computing time in R
I would suggest a couple of links:
1) Shrink number of levels of a factor variable
is a link to a question on stackoverflow to deal with a similar issue while using the randomForest package. Specifically it deals with using only the most frequently occurring levels and assigning a n... | Random forest computing time in R
I would suggest a couple of links:
1) Shrink number of levels of a factor variable
is a link to a question on stackoverflow to deal with a similar issue while using the randomForest package. Specif |
4,381 | How to decide on the correct number of clusters? | This has been asked a couple of times on stackoverflow: here, here and here. You can take a look at what the crowd over there thinks about this question (or a small variant thereof).
Let me also copy my own answer to this question, on stackoverflow.com:
Unfortunately there is no way to automatically set the "right" K n... | How to decide on the correct number of clusters? | This has been asked a couple of times on stackoverflow: here, here and here. You can take a look at what the crowd over there thinks about this question (or a small variant thereof).
Let me also copy | How to decide on the correct number of clusters?
This has been asked a couple of times on stackoverflow: here, here and here. You can take a look at what the crowd over there thinks about this question (or a small variant thereof).
Let me also copy my own answer to this question, on stackoverflow.com:
Unfortunately the... | How to decide on the correct number of clusters?
This has been asked a couple of times on stackoverflow: here, here and here. You can take a look at what the crowd over there thinks about this question (or a small variant thereof).
Let me also copy |
4,382 | How to decide on the correct number of clusters? | Firstly a caveat. In clustering there is often no one "correct answer" - one clustering may be better than another by one metric, and the reverse may be true using another metric. And in some situations two different clusterings could be equally probable under the same metric.
Having said that, you might want to have a... | How to decide on the correct number of clusters? | Firstly a caveat. In clustering there is often no one "correct answer" - one clustering may be better than another by one metric, and the reverse may be true using another metric. And in some situatio | How to decide on the correct number of clusters?
Firstly a caveat. In clustering there is often no one "correct answer" - one clustering may be better than another by one metric, and the reverse may be true using another metric. And in some situations two different clusterings could be equally probable under the same m... | How to decide on the correct number of clusters?
Firstly a caveat. In clustering there is often no one "correct answer" - one clustering may be better than another by one metric, and the reverse may be true using another metric. And in some situatio |
4,383 | How to decide on the correct number of clusters? | I use the Elbow method:
Start with K=2, and keep increasing it in each step by 1, calculating your clusters and the cost that comes with the training. At some value for K the cost drops dramatically, and after that it reaches a plateau when you increase it further. This is the K value you want.
The rationale is that ... | How to decide on the correct number of clusters? | I use the Elbow method:
Start with K=2, and keep increasing it in each step by 1, calculating your clusters and the cost that comes with the training. At some value for K the cost drops dramatically, | How to decide on the correct number of clusters?
I use the Elbow method:
Start with K=2, and keep increasing it in each step by 1, calculating your clusters and the cost that comes with the training. At some value for K the cost drops dramatically, and after that it reaches a plateau when you increase it further. This... | How to decide on the correct number of clusters?
I use the Elbow method:
Start with K=2, and keep increasing it in each step by 1, calculating your clusters and the cost that comes with the training. At some value for K the cost drops dramatically, |
4,384 | How to decide on the correct number of clusters? | Cluster sizes depend highly on both your data and what you're gonna use the results for. If your using your data for splitting things into categories, try to imagine how many categories you want first. If it's for data visualization, make it configurable, so people can see both the large clusters and the smaller ones.
... | How to decide on the correct number of clusters? | Cluster sizes depend highly on both your data and what you're gonna use the results for. If your using your data for splitting things into categories, try to imagine how many categories you want first | How to decide on the correct number of clusters?
Cluster sizes depend highly on both your data and what you're gonna use the results for. If your using your data for splitting things into categories, try to imagine how many categories you want first. If it's for data visualization, make it configurable, so people can s... | How to decide on the correct number of clusters?
Cluster sizes depend highly on both your data and what you're gonna use the results for. If your using your data for splitting things into categories, try to imagine how many categories you want first |
4,385 | How to decide on the correct number of clusters? | You can also check Unsupervised Optimal Fuzzy Clustering which deal with the problem you have mentioned (finding the number of clusters) which a modified version of it is implemented here | How to decide on the correct number of clusters? | You can also check Unsupervised Optimal Fuzzy Clustering which deal with the problem you have mentioned (finding the number of clusters) which a modified version of it is implemented here | How to decide on the correct number of clusters?
You can also check Unsupervised Optimal Fuzzy Clustering which deal with the problem you have mentioned (finding the number of clusters) which a modified version of it is implemented here | How to decide on the correct number of clusters?
You can also check Unsupervised Optimal Fuzzy Clustering which deal with the problem you have mentioned (finding the number of clusters) which a modified version of it is implemented here |
4,386 | How to decide on the correct number of clusters? | I have managed to use the "L Method" to determine the number of clusters in a geographic application (ie. essentally a 2d problem although technically non-Euclidean).
The L Method is described here:
Determining the Number of Clusters/Segments in Hierarchical Clustering/Segmentation Algorithms Stan Salvador and Philip ... | How to decide on the correct number of clusters? | I have managed to use the "L Method" to determine the number of clusters in a geographic application (ie. essentally a 2d problem although technically non-Euclidean).
The L Method is described here:
| How to decide on the correct number of clusters?
I have managed to use the "L Method" to determine the number of clusters in a geographic application (ie. essentally a 2d problem although technically non-Euclidean).
The L Method is described here:
Determining the Number of Clusters/Segments in Hierarchical Clustering/... | How to decide on the correct number of clusters?
I have managed to use the "L Method" to determine the number of clusters in a geographic application (ie. essentally a 2d problem although technically non-Euclidean).
The L Method is described here:
|
4,387 | How to decide on the correct number of clusters? | You need to reconsider what k-means does. It tries to find the optimal Voronoi partitioning of the data set into $k$ cells. Voronoi cells are oddly shaped cells, the orthogonal structure of a Delaunay triangulation.
But what if your data set doesn't actually fit into the Voronoi scheme?
Most likely, the actual clusters... | How to decide on the correct number of clusters? | You need to reconsider what k-means does. It tries to find the optimal Voronoi partitioning of the data set into $k$ cells. Voronoi cells are oddly shaped cells, the orthogonal structure of a Delaunay | How to decide on the correct number of clusters?
You need to reconsider what k-means does. It tries to find the optimal Voronoi partitioning of the data set into $k$ cells. Voronoi cells are oddly shaped cells, the orthogonal structure of a Delaunay triangulation.
But what if your data set doesn't actually fit into the... | How to decide on the correct number of clusters?
You need to reconsider what k-means does. It tries to find the optimal Voronoi partitioning of the data set into $k$ cells. Voronoi cells are oddly shaped cells, the orthogonal structure of a Delaunay |
4,388 | How to decide on the correct number of clusters? | As no one has pointed it yet, I thought I would share this. There is a method called X-means, (see this link) which estimates proper number of clusters using Bayesian information criterion (BIC). Essentially, this would be like trying K means with different Ks, calculating BIC for each K and choosing the best K. This a... | How to decide on the correct number of clusters? | As no one has pointed it yet, I thought I would share this. There is a method called X-means, (see this link) which estimates proper number of clusters using Bayesian information criterion (BIC). Esse | How to decide on the correct number of clusters?
As no one has pointed it yet, I thought I would share this. There is a method called X-means, (see this link) which estimates proper number of clusters using Bayesian information criterion (BIC). Essentially, this would be like trying K means with different Ks, calculati... | How to decide on the correct number of clusters?
As no one has pointed it yet, I thought I would share this. There is a method called X-means, (see this link) which estimates proper number of clusters using Bayesian information criterion (BIC). Esse |
4,389 | How to decide on the correct number of clusters? | Overall, you can choose number of clusters in in two different paths.
knowledge driven: you should have some ideas how many cluster do you need from business point of view. For example, you are clustering customers, you should ask yourself, after getting these customers, what should I do next? May be you will have dif... | How to decide on the correct number of clusters? | Overall, you can choose number of clusters in in two different paths.
knowledge driven: you should have some ideas how many cluster do you need from business point of view. For example, you are clust | How to decide on the correct number of clusters?
Overall, you can choose number of clusters in in two different paths.
knowledge driven: you should have some ideas how many cluster do you need from business point of view. For example, you are clustering customers, you should ask yourself, after getting these customers... | How to decide on the correct number of clusters?
Overall, you can choose number of clusters in in two different paths.
knowledge driven: you should have some ideas how many cluster do you need from business point of view. For example, you are clust |
4,390 | How to decide on the correct number of clusters? | Rather than use some statistical criteria (although those may be useful) I would base it on utility for the problem at hand.
Look at various solutions and then judge which one best answers your research question or your business need or else which one gives you insight into the data. So, in one situation, you might cho... | How to decide on the correct number of clusters? | Rather than use some statistical criteria (although those may be useful) I would base it on utility for the problem at hand.
Look at various solutions and then judge which one best answers your resear | How to decide on the correct number of clusters?
Rather than use some statistical criteria (although those may be useful) I would base it on utility for the problem at hand.
Look at various solutions and then judge which one best answers your research question or your business need or else which one gives you insight i... | How to decide on the correct number of clusters?
Rather than use some statistical criteria (although those may be useful) I would base it on utility for the problem at hand.
Look at various solutions and then judge which one best answers your resear |
4,391 | How to decide on the correct number of clusters? | Another approach is to use an evolutionary algorithm whose individuals have chromosomes of different lengths. Each individual is a candidate solution: each one carries the centroids coordinates. The number of centroids and their coordinates are evolved in order to reach a solution that yields the best clustering evalua... | How to decide on the correct number of clusters? | Another approach is to use an evolutionary algorithm whose individuals have chromosomes of different lengths. Each individual is a candidate solution: each one carries the centroids coordinates. The n | How to decide on the correct number of clusters?
Another approach is to use an evolutionary algorithm whose individuals have chromosomes of different lengths. Each individual is a candidate solution: each one carries the centroids coordinates. The number of centroids and their coordinates are evolved in order to reach ... | How to decide on the correct number of clusters?
Another approach is to use an evolutionary algorithm whose individuals have chromosomes of different lengths. Each individual is a candidate solution: each one carries the centroids coordinates. The n |
4,392 | What is perplexity? | You have looked at the Wikipedia article on perplexity. It gives the perplexity of a discrete distribution as
$$2^{-\sum_x p(x)\log_2 p(x)}$$
which could also be written as
$$\exp\left({\sum_x p(x)\log_e \frac{1}{p(x)}}\right)$$
i.e. as a weighted geometric average of the inverses of the probabilities. For a conti... | What is perplexity? | You have looked at the Wikipedia article on perplexity. It gives the perplexity of a discrete distribution as
$$2^{-\sum_x p(x)\log_2 p(x)}$$
which could also be written as
$$\exp\left({\sum_x p(x) | What is perplexity?
You have looked at the Wikipedia article on perplexity. It gives the perplexity of a discrete distribution as
$$2^{-\sum_x p(x)\log_2 p(x)}$$
which could also be written as
$$\exp\left({\sum_x p(x)\log_e \frac{1}{p(x)}}\right)$$
i.e. as a weighted geometric average of the inverses of the probab... | What is perplexity?
You have looked at the Wikipedia article on perplexity. It gives the perplexity of a discrete distribution as
$$2^{-\sum_x p(x)\log_2 p(x)}$$
which could also be written as
$$\exp\left({\sum_x p(x) |
4,393 | What is perplexity? | I found this rather intuitive:
The perplexity of whatever you're evaluating, on the data you're
evaluating it on, sort of tells you "this thing is right about as
often as an x-sided die would be."
http://planspace.org/2013/09/23/perplexity-what-it-is-and-what-yours-is/ | What is perplexity? | I found this rather intuitive:
The perplexity of whatever you're evaluating, on the data you're
evaluating it on, sort of tells you "this thing is right about as
often as an x-sided die would be. | What is perplexity?
I found this rather intuitive:
The perplexity of whatever you're evaluating, on the data you're
evaluating it on, sort of tells you "this thing is right about as
often as an x-sided die would be."
http://planspace.org/2013/09/23/perplexity-what-it-is-and-what-yours-is/ | What is perplexity?
I found this rather intuitive:
The perplexity of whatever you're evaluating, on the data you're
evaluating it on, sort of tells you "this thing is right about as
often as an x-sided die would be. |
4,394 | What is perplexity? | I've wondered this too. The first explanation isn't bad, but here are my 2 nats for whatever that's worth.
First of all, perplexity has nothing to do with characterizing how often you guess something right. It has more to do with characterizing the complexity of a stochastic sequence.
We're looking at a quantity, $$2^... | What is perplexity? | I've wondered this too. The first explanation isn't bad, but here are my 2 nats for whatever that's worth.
First of all, perplexity has nothing to do with characterizing how often you guess something | What is perplexity?
I've wondered this too. The first explanation isn't bad, but here are my 2 nats for whatever that's worth.
First of all, perplexity has nothing to do with characterizing how often you guess something right. It has more to do with characterizing the complexity of a stochastic sequence.
We're looking... | What is perplexity?
I've wondered this too. The first explanation isn't bad, but here are my 2 nats for whatever that's worth.
First of all, perplexity has nothing to do with characterizing how often you guess something |
4,395 | What is perplexity? | There is actually a clear connection between perplexity and the odds of correctly guessing a value from a distribution, given by Cover's Elements of Information Theory 2ed (2.146): If $X$ and $X'$ are iid variables, then
$P(X=X') \ge 2^{-H(X)} = \frac{1}{2^{H(X)}} = \frac{1}{\text{perplexity}}$ (1)
To explain, perplex... | What is perplexity? | There is actually a clear connection between perplexity and the odds of correctly guessing a value from a distribution, given by Cover's Elements of Information Theory 2ed (2.146): If $X$ and $X'$ are | What is perplexity?
There is actually a clear connection between perplexity and the odds of correctly guessing a value from a distribution, given by Cover's Elements of Information Theory 2ed (2.146): If $X$ and $X'$ are iid variables, then
$P(X=X') \ge 2^{-H(X)} = \frac{1}{2^{H(X)}} = \frac{1}{\text{perplexity}}$ (1)... | What is perplexity?
There is actually a clear connection between perplexity and the odds of correctly guessing a value from a distribution, given by Cover's Elements of Information Theory 2ed (2.146): If $X$ and $X'$ are |
4,396 | Why do we only see $L_1$ and $L_2$ regularization but not other norms? | In addition to @whuber's comments (*).
The book by Hastie et al Statistical learning with Sparsity discusses this. They also uses what is called the $L_0$ "norm" (quotation marks because this is not a norm in the strict mathematical sense (**)), which simply counts the number of nonzero components of a vector.
In that... | Why do we only see $L_1$ and $L_2$ regularization but not other norms? | In addition to @whuber's comments (*).
The book by Hastie et al Statistical learning with Sparsity discusses this. They also uses what is called the $L_0$ "norm" (quotation marks because this is not | Why do we only see $L_1$ and $L_2$ regularization but not other norms?
In addition to @whuber's comments (*).
The book by Hastie et al Statistical learning with Sparsity discusses this. They also uses what is called the $L_0$ "norm" (quotation marks because this is not a norm in the strict mathematical sense (**)), wh... | Why do we only see $L_1$ and $L_2$ regularization but not other norms?
In addition to @whuber's comments (*).
The book by Hastie et al Statistical learning with Sparsity discusses this. They also uses what is called the $L_0$ "norm" (quotation marks because this is not |
4,397 | Why do we only see $L_1$ and $L_2$ regularization but not other norms? | I think the answer to the question depends a lot on how you define "better." If I'm interpreting right, you want to know why it is that these norms appear so frequently as compared to other options. In this case, the answer is simplicity. The intuition behind regularization is that I have some vector, and I would like ... | Why do we only see $L_1$ and $L_2$ regularization but not other norms? | I think the answer to the question depends a lot on how you define "better." If I'm interpreting right, you want to know why it is that these norms appear so frequently as compared to other options. I | Why do we only see $L_1$ and $L_2$ regularization but not other norms?
I think the answer to the question depends a lot on how you define "better." If I'm interpreting right, you want to know why it is that these norms appear so frequently as compared to other options. In this case, the answer is simplicity. The intuit... | Why do we only see $L_1$ and $L_2$ regularization but not other norms?
I think the answer to the question depends a lot on how you define "better." If I'm interpreting right, you want to know why it is that these norms appear so frequently as compared to other options. I |
4,398 | Why do we only see $L_1$ and $L_2$ regularization but not other norms? | The main reason for seeing mostly $L_1$ and $L_2$ norms is that they cover the majority of current applications. For example, the norm $L_1$ also called the taxicab norm, a lattice rectilinear connecting norm, includes the absolute value norm.
$L_2$ norms are, in addition to least squares, Euclidean distances in $n$-sp... | Why do we only see $L_1$ and $L_2$ regularization but not other norms? | The main reason for seeing mostly $L_1$ and $L_2$ norms is that they cover the majority of current applications. For example, the norm $L_1$ also called the taxicab norm, a lattice rectilinear connect | Why do we only see $L_1$ and $L_2$ regularization but not other norms?
The main reason for seeing mostly $L_1$ and $L_2$ norms is that they cover the majority of current applications. For example, the norm $L_1$ also called the taxicab norm, a lattice rectilinear connecting norm, includes the absolute value norm.
$L_2$... | Why do we only see $L_1$ and $L_2$ regularization but not other norms?
The main reason for seeing mostly $L_1$ and $L_2$ norms is that they cover the majority of current applications. For example, the norm $L_1$ also called the taxicab norm, a lattice rectilinear connect |
4,399 | Mathematical Statistics Videos | Check out the following links. I'm not sure what exactly are you looking for.
Monte Carlo Simulation for Statistical Inference
Kernel methods and Support Vector Machines
Introduction to Support Vector Machines
Monte Carlo Simulations
Free Science and Video Lectures Online!
Video lectures on Machine Learning | Mathematical Statistics Videos | Check out the following links. I'm not sure what exactly are you looking for.
Monte Carlo Simulation for Statistical Inference
Kernel methods and Support Vector Machines
Introduction to Support Vector | Mathematical Statistics Videos
Check out the following links. I'm not sure what exactly are you looking for.
Monte Carlo Simulation for Statistical Inference
Kernel methods and Support Vector Machines
Introduction to Support Vector Machines
Monte Carlo Simulations
Free Science and Video Lectures Online!
Video lectures ... | Mathematical Statistics Videos
Check out the following links. I'm not sure what exactly are you looking for.
Monte Carlo Simulation for Statistical Inference
Kernel methods and Support Vector Machines
Introduction to Support Vector |
4,400 | Mathematical Statistics Videos | See Videos on data analysis using R on Jeromy Anglim's blog. There are many links at that page and he updates it. He has another post with many links to videos on probability and statistics as well as linear algebra and calculus. | Mathematical Statistics Videos | See Videos on data analysis using R on Jeromy Anglim's blog. There are many links at that page and he updates it. He has another post with many links to videos on probability and statistics as well | Mathematical Statistics Videos
See Videos on data analysis using R on Jeromy Anglim's blog. There are many links at that page and he updates it. He has another post with many links to videos on probability and statistics as well as linear algebra and calculus. | Mathematical Statistics Videos
See Videos on data analysis using R on Jeromy Anglim's blog. There are many links at that page and he updates it. He has another post with many links to videos on probability and statistics as well |
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