Id stringlengths 1 6 | PostTypeId stringclasses 7
values | AcceptedAnswerId stringlengths 1 6 ⌀ | ParentId stringlengths 1 6 ⌀ | Score stringlengths 1 4 | ViewCount stringlengths 1 7 ⌀ | Body stringlengths 0 38.7k | Title stringlengths 15 150 ⌀ | ContentLicense stringclasses 3
values | FavoriteCount stringclasses 3
values | CreationDate stringlengths 23 23 | LastActivityDate stringlengths 23 23 | LastEditDate stringlengths 23 23 ⌀ | LastEditorUserId stringlengths 1 6 ⌀ | OwnerUserId stringlengths 1 6 ⌀ | Tags list |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1839 | 2 | null | 1829 | 4 | null | I tend to think of 'least squares' as a criterion for defining the best fitting regression line (i.e., that which makes the sum of 'squared' residuals 'least') and the 'algorithm' in this context as the set of steps used to determine the regression coefficients that satisfy that criterion. This distinction suggests tha... | null | CC BY-SA 2.5 | null | 2010-08-18T14:57:00.733 | 2010-08-18T14:57:00.733 | null | null | 183 | null |
1840 | 2 | null | 1826 | 6 | null | Let's say you investigate some process; you've gathered some data describing it and you have build a model (either statistical or ML, doesn't matter). But now, how to judge if it is ok? Probably it fits suspiciously good to the data it was build on, so no-one will believe that your model is so splendid that you think.
... | null | CC BY-SA 2.5 | null | 2010-08-18T15:14:02.023 | 2010-08-18T15:14:02.023 | null | null | null | null |
1841 | 1 | 2057 | null | 8 | 662 | Disclaimer: I'm a software engineer, not a statistician, so please forgive any blunt error :-)
I have a set of time-series "curves", each measuring the entropy of a given artifact. Now, I'm standing over the following premises (please criticize them as you see fit):
- In order to approximate the upper bounds of the Ko... | Hypothesis testing that one time-series of a measure of entropy doesn't belong to a population | CC BY-SA 2.5 | null | 2010-08-18T15:19:44.807 | 2010-08-25T13:52:20.933 | 2010-08-18T16:00:37.460 | 990 | 990 | [
"r",
"time-series",
"hypothesis-testing",
"spss",
"entropy"
] |
1842 | 2 | null | 1838 | 12 | null | I think you can get what you want using `ggplot2`. Using the code below, I can produce:
Obviously things like line colours can be changed to what ever you want. On the x-axis I specified major lines on years and minor lines on months.
```
require(ggplot2)
t = as.Date(0:1... | null | CC BY-SA 2.5 | null | 2010-08-18T15:25:59.757 | 2010-08-18T15:25:59.757 | null | null | 8 | null |
1843 | 2 | null | 1838 | 16 | null | You can use `par(new=TRUE)` to plot into the same graph using two different y-axes! This should also solve your problem.
Next you will find a simple example that plots two random normal variables, one on mean 0 the other one on mean 100 (both sd s = 1) in the same plot. The first one in red on the left y-axis, the seco... | null | CC BY-SA 3.0 | null | 2010-08-18T15:43:03.723 | 2013-11-16T01:50:25.777 | 2013-11-16T01:50:25.777 | 442 | 442 | null |
1844 | 1 | 2053 | null | 18 | 12148 | One way to summarize the comparison of two survival curves is to compute the hazard ratio (HR). There are (at least) two methods to compute this value.
- Logrank method. As part of the Kaplan-Meier calculations, compute the number of observed events (deaths, usually) in each group ($Oa$, and $Ob$), and the number of ... | What are the pros and cons of using the logrank vs. the Mantel-Haenszel method for computing the Hazard Ratio in survival analysis? | CC BY-SA 3.0 | null | 2010-08-18T15:47:15.627 | 2013-05-25T15:42:51.127 | 2013-05-25T15:42:51.127 | 7290 | 25 | [
"survival",
"hazard"
] |
1845 | 2 | null | 1829 | 35 | null | Regarding the question in the title, about what is the algorithm that is used:
In a linear algebra perspective, the linear regression algorithm is the way to solve a linear system $\mathbf{A}x=b$ with more equations than unknowns. In most of the cases there is no solution to this problem. And this is because the vector... | null | CC BY-SA 3.0 | null | 2010-08-18T16:19:28.490 | 2011-12-04T07:53:22.947 | 2011-12-04T07:53:22.947 | 2914 | 339 | null |
1846 | 2 | null | 1376 | 2 | null | Some robust alernatives are discussed in [A class of robust stepwise alternativese to Hotelling's T 2 tests](http://dx.doi.org/10.1080/02664760050076434), which deals with trimmed means of the marginals of residuals produced by stepwise regression, and in [A comparison of robust alternatives to Hoteslling's T^2 control... | null | CC BY-SA 2.5 | null | 2010-08-18T16:28:57.907 | 2010-08-18T16:28:57.907 | null | null | 795 | null |
1847 | 2 | null | 1787 | 3 | null | Have you thought about using simulate in the arm package? Gelman & Hill have some nice chapters on this in their book.
| null | CC BY-SA 2.5 | null | 2010-08-18T16:38:48.443 | 2010-08-18T16:38:48.443 | null | null | 101 | null |
1848 | 1 | 1849 | null | 9 | 2126 | I'm implementing a rating system to be used on my website, and I think the Bayesian average is the best way to go about it. Every item will be rated in six different categories by the users. I don't want items with only one high rating to shoot to the top though, which is why I want to implement a Bayesian system.
Here... | Bayesian rating system with multiple categories for each rating | CC BY-SA 2.5 | null | 2010-08-18T16:43:11.870 | 2014-01-31T15:08:16.867 | null | null | 991 | [
"bayesian"
] |
1849 | 2 | null | 1848 | 6 | null | It depends on whether you want to wind up only with a cumulative rating of each object, or category-specific rating. Having a separate system in each category sounds more realistic, but your particular context might suggest otherwise. You could even do both a category-specific and overall rating!
| null | CC BY-SA 2.5 | null | 2010-08-18T16:58:10.540 | 2010-08-18T16:58:10.540 | null | null | 279 | null |
1850 | 1 | 1930 | null | 32 | 91771 | For an effect size analysis, I am noticing that there are differences between Cohen's d, Hedges's g and Hedges' g*.
- Are these three metrics normally very similar?
- What would be a case where they would produce different results?
- Also is it a matter of preference which I use or report with?
| Difference between Cohen's d and Hedges' g for effect size metrics | CC BY-SA 2.5 | null | 2010-08-18T17:35:17.280 | 2020-11-03T20:02:33.500 | 2010-08-19T08:02:01.917 | 183 | 559 | [
"effect-size",
"cohens-d"
] |
1852 | 2 | null | 1807 | 3 | null | Suppose there are 999 workers at ACME north factory each making a wage of 112, and 1 CEO making 88112. The population mean salary is $\mu = 0.999 * 112 + 0.001 * 88112 = 200.$ The probability of drawing the CEO from a sample of 49 people at the factory is $49 / 1000 < 0.05$ (this is from the hypergeometric distribution... | null | CC BY-SA 2.5 | null | 2010-08-18T18:21:12.870 | 2010-08-19T17:09:15.637 | 2010-08-19T17:09:15.637 | 795 | 795 | null |
1853 | 1 | 1953 | null | 13 | 2510 | What tests are available for testing two independent samples for the null hypothesis that they come from populations with the same skew? There is a classical 1-sample test for whether the skew equals a fixed number (the test involves the 6th sample moment!); is there a straightforward translation to a 2-sample test?
A... | Testing two independent samples for null of same skew? | CC BY-SA 2.5 | null | 2010-08-18T18:49:48.227 | 2015-09-16T07:58:23.800 | 2015-09-16T07:58:23.800 | 11887 | 795 | [
"hypothesis-testing",
"distributions",
"bootstrap",
"moments",
"l-moments"
] |
1854 | 2 | null | 1826 | 10 | null | "Avoid learning your training data by heart by making sure the trained model performs well on independent data."
| null | CC BY-SA 2.5 | null | 2010-08-18T19:09:37.983 | 2010-08-18T19:09:37.983 | null | null | 961 | null |
1855 | 2 | null | 1797 | 7 | null | It has the same meaning as any other confidence interval: under the assumption that the model is correct, if the experiment and procedure is repeated over and over, 95% of the time the true value of the quantity of interest will lie within the interval. In this case, the quantity of interest is the expected value of th... | null | CC BY-SA 2.5 | null | 2010-08-18T19:16:05.037 | 2010-08-18T19:16:05.037 | null | null | 495 | null |
1856 | 1 | 2888 | null | 17 | 4618 | What do you think about applying machine learning techniques, like Random Forests or penalized regression (with L1 or L2 penalty, or a combination thereof) in small sample clinical studies when the objective is to isolate interesting predictors in a classification context? It is not a question about model selection, no... | Application of machine learning techniques in small sample clinical studies | CC BY-SA 2.5 | null | 2010-08-18T20:36:59.617 | 2015-06-20T20:44:31.313 | 2010-09-19T10:57:54.697 | 930 | 930 | [
"machine-learning",
"feature-selection"
] |
1857 | 2 | null | 1856 | 4 | null | One common rule of thumb is to have at least 10 times the number of training data instances (not to speak of any test/validation data, etc.) as there are adjustable parameters in the classifier. Keep in mind that you have a problem wherein you need to not only have adequate data but also representative data. In the e... | null | CC BY-SA 2.5 | null | 2010-08-18T20:51:32.280 | 2010-08-18T21:23:54.503 | 2010-08-18T21:23:54.503 | 5 | 5 | null |
1858 | 2 | null | 1856 | 3 | null | I can assure you that RF would work in that case and its importance measure would be pretty insightful (because there will be no large tail of misleading unimportant attributes like in standard (n << p)s). I can't recall now any paper dealing with similar problem, but I'll look for it.
| null | CC BY-SA 2.5 | null | 2010-08-18T21:28:17.517 | 2010-08-18T21:28:17.517 | null | null | null | null |
1860 | 1 | 1861 | null | 4 | 126 | I am studying a population of individuals who all begin with a measureable score of interest (ranging from -2 to 2) [call it "old"], then they all undergo a change to a new score (also ranging from -2 to 2) ["new"]. Thus all the variation is in the change (which can be positive or negative), and there are also a variet... | Regression specification choices | CC BY-SA 2.5 | null | 2010-08-18T22:58:05.027 | 2010-08-19T12:59:30.587 | null | null | 78 | [
"regression"
] |
1861 | 2 | null | 1860 | 3 | null | You are right, version 1 is not acceptable. The second or third options (as long as `old` has a coefficient that will be estimated) are both OK, and in fact equivalent with respect to estimates for `a` and `b`. This can be seen if you replace `change` with `new-old` in the second equation, and solve it for `new`. All t... | null | CC BY-SA 2.5 | null | 2010-08-18T23:17:46.677 | 2010-08-19T12:59:30.587 | 2010-08-19T12:59:30.587 | 279 | 279 | null |
1862 | 1 | 1869 | null | 13 | 8268 | I've been struggling with the following problem with hopefully is an easy one for statisticians (I'm a programmer with some exposure to statistics).
I need to summarize the responses to a survey (for management). The survey has 100+ questions, grouped in different areas (with about 5 to 10 questions per area). All answ... | How to summarize categorical data? | CC BY-SA 3.0 | null | 2010-08-19T00:31:44.013 | 2017-07-14T08:29:38.673 | 2017-07-14T08:29:38.673 | 11887 | 840 | [
"categorical-data",
"data-transformation",
"descriptive-statistics"
] |
1863 | 1 | 1871 | null | 6 | 1617 | I ran a within subjects repeated measures experiment, where the independent variable had 3 levels. The dependent variable is a measure of correctness and is recorded as either correct / incorrect. Time taken to provide an answer was also recorded.
A within subjects repeated measures ANOVA is used to establish whether t... | Might be an unbalanced within subjects repeated measures? | CC BY-SA 2.5 | null | 2010-08-19T00:50:20.120 | 2010-08-21T07:21:06.203 | null | null | 993 | [
"variance",
"unbalanced-classes",
"repeated-measures"
] |
1864 | 2 | null | 1856 | 5 | null | I would have very little confidence in the generalisability of results of an exploratory analysis with 15 predictors and a sample size of 20.
- The confidence intervals of parameter estimates would be large. E.g., the 95% confidence interval on r = .30 with n = 20 is -0.17 to 0.66 .
- Issues tend to be compounded whe... | null | CC BY-SA 2.5 | null | 2010-08-19T00:59:56.543 | 2010-08-19T05:53:41.183 | 2010-08-19T05:53:41.183 | 183 | 183 | null |
1865 | 1 | null | null | 7 | 1201 | Standard deck has 52 cards, 26 Red and 26 Black. A run is a maximum contiguous block of cards, which has the same color.
Eg.
- (R,B,R,B,...,R,B) has 52 runs.
- (R,R,R,...,R,B,B,B,...,B) has 2 runs.
What is the expected number of runs in a shuffled deck of cards?
| What is the expected number of runs of same color in a standard deck of cards? | CC BY-SA 2.5 | null | 2010-08-19T01:15:27.043 | 2023-04-18T10:58:32.437 | 2010-09-19T16:20:20.837 | null | 994 | [
"probability",
"games"
] |
1866 | 1 | 1918 | null | 13 | 4633 | Following to the recent questions we had [here](https://stats.stackexchange.com/questions/1818/how-to-determine-the-sample-size-needed-for-repeated-measurement-anova/1823#1823).
I was hopping to know if anyone had come across or can share R code for performing a custom power analysis based on simulation for a linear mo... | How to simulate a custom power analysis of an lm model (using R)? | CC BY-SA 4.0 | null | 2010-08-19T02:10:15.867 | 2021-08-19T18:16:33.700 | 2021-08-19T18:08:54.867 | 11887 | 253 | [
"r",
"simulation",
"statistical-power"
] |
1867 | 2 | null | 1863 | 2 | null | So this is a one way repeated measures Anova - with the "Y" being time till answer was given, and the first factor having 3 levels (each subject having three of them).
I think the easiest way for doing this would be to take the mean response time for each subject for each of the three levels (which will results in 3 nu... | null | CC BY-SA 2.5 | null | 2010-08-19T02:35:58.207 | 2010-08-19T02:35:58.207 | null | null | 253 | null |
1868 | 2 | null | 1860 | 2 | null | A few references that you might find useful:
- Edwards (2001) has a nice article called Ten Difference Score Myths.
- I have a post with some general points on change scores.
| null | CC BY-SA 2.5 | null | 2010-08-19T03:03:39.437 | 2010-08-19T03:03:39.437 | null | null | 183 | null |
1869 | 2 | null | 1862 | 10 | null | You really need to figure out what is the question that you are trying to answer- or what question is management most interested in. Then you can select the survey questions that are most relevant to your problem.
Without knowing anything about your problem or dataset, here are some generic solutions:
- Visually repr... | null | CC BY-SA 2.5 | null | 2010-08-19T03:15:34.427 | 2010-08-19T03:21:26.100 | 2010-08-19T03:21:26.100 | 995 | 995 | null |
1870 | 1 | 1879 | null | 8 | 875 | The question is in the header, but I would extend the context a bit.
Next semester I am due to be a teaching assistant (TA) in a course in statistics, where I would need to help sociology students learn to use SPSS. I don't know SPSS, yet, and would like to learn how to use it.
I was thinking of taking a simple dataset... | Learning how to use a new statistical GUI? | CC BY-SA 3.0 | null | 2010-08-19T04:35:15.690 | 2016-12-19T21:47:15.810 | 2016-12-19T21:47:15.810 | 22468 | 253 | [
"spss",
"references",
"software",
"teaching"
] |
1871 | 2 | null | 1863 | 3 | null | It's not imbalanced because your repeated measures should be averaged across such subgroups within subject beforehand. The only thing imbalanced is the quality of the estimates of your means.
Just as you aggregated your accuracies to get a percentage correct and do your ANOVA in the first place you average your latenc... | null | CC BY-SA 2.5 | null | 2010-08-19T04:35:45.863 | 2010-08-21T07:21:06.203 | 2010-08-21T07:21:06.203 | 601 | 601 | null |
1872 | 2 | null | 1870 | 6 | null | Since you are pretty well versed in R, get a copy of Muenchen's "[R for SAS and SPSS Users](http://www.springer.com/statistics/computanional+statistics/book/978-0-387-09417-5)" (Springer, 2009) and work backwards.
| null | CC BY-SA 2.5 | null | 2010-08-19T04:47:46.457 | 2010-08-19T04:47:46.457 | null | null | 597 | null |
1873 | 1 | null | null | 3 | 194 | I posted this on mathoverflow, but they sent me here. This question relates to a problem I had at work a while ago, doing a little data mining at a car rental company. Names changed, of course. I'm using Oracle DBMS if it matters.
There was a flight of steps out the front of our building. It had a dodgy step on it, on ... | Based on my data, is Jack likely to be clumsy? | CC BY-SA 2.5 | null | 2010-08-19T04:50:25.533 | 2010-09-16T06:49:06.127 | 2010-09-16T06:49:06.127 | null | 997 | [
"hypothesis-testing"
] |
1874 | 1 | null | null | 5 | 167 | I'm looking to construct a 3-D surface of a part of the brain based on 2-D contours from cross-sectional slices from multiple angles. Once I get this shape, I want to "fit" it to another set of contours via rescaling.
I'm aspiring to do this in the context of an MCMC analysis (So as to be able to make inferences, so it... | Parametric Surface Reconstruction from Contours with Quick Rescaling | CC BY-SA 2.5 | null | 2010-08-19T04:53:32.270 | 2010-10-12T18:11:52.460 | null | null | 996 | [
"bayesian",
"markov-chain-montecarlo",
"fitting",
"optimal-scaling",
"interpolation"
] |
1875 | 1 | 1903 | null | 21 | 1443 | A question which bothered me for some time, which I don't know how to address:
Every day, my weatherman gives a percentage chance of rain (let's assume its calculated to 9000 digits and he has never repeated a number). Every subsequent day, it either rains or does not rain.
I have years of data - pct chance vs rain or ... | Is my weatherman accurate? | CC BY-SA 2.5 | null | 2010-08-19T05:56:06.483 | 2020-12-26T15:49:48.700 | 2020-12-26T15:49:48.700 | 11887 | 997 | [
"hypothesis-testing",
"forecasting",
"scoring-rules"
] |
1876 | 2 | null | 1862 | 8 | null | Standard options include:
- getting the mean for items within a scale (e.g., if the scale is 1 to 5, the mean will be 1 to 5)
- converting each item to a binary measure (e.g., if item >= 3, then 1, else 0) and then taking the mean of this binary response
Given that you are aggregating over items and over large samp... | null | CC BY-SA 2.5 | null | 2010-08-19T06:13:02.550 | 2010-08-19T06:13:02.550 | null | null | 183 | null |
1877 | 2 | null | 1873 | 3 | null | ```
chisq.test(c(15,7),p=c(3000,1000),rescale.p=TRUE)
Chi-squared test for given probabilities
data: c(15, 7)
X-squared = 0.5455, df = 1, p-value = 0.4602
```
There is not enough evidence against the Null hypothesis (that is just a random incident).
A difference from the expected value as big as or bigger than ... | null | CC BY-SA 2.5 | null | 2010-08-19T06:16:25.087 | 2010-08-19T06:29:38.990 | 2010-08-19T06:29:38.990 | 339 | 339 | null |
1878 | 2 | null | 1875 | 11 | null | Comparison of probability forecast for binary event (or discrete Random Variable) can be done upon the [Brier score](http://en.wikipedia.org/wiki/Brier_score)
but you can also use [ROC curve](http://en.wikipedia.org/wiki/Receiver_operating_characteristic) since any probability forecast of this type can be transformed... | null | CC BY-SA 2.5 | null | 2010-08-19T06:22:09.973 | 2011-01-25T18:19:47.763 | 2011-01-25T18:19:47.763 | 223 | 223 | null |
1879 | 2 | null | 1870 | 11 | null | As someone who made the shift the other way from SPSS to R, I'd say that SPSS is relatively simple and intuitive relative to R. The menus and dialog boxes guide you through the process. Of course this means that it is also fairly easy to run analyses that don't make sense. And the GUI leads to less flexible analyses a... | null | CC BY-SA 2.5 | null | 2010-08-19T06:28:05.217 | 2010-08-19T06:28:05.217 | null | null | 183 | null |
1880 | 2 | null | 1866 | 3 | null | Here are a few sources of simulation code in R. I'm not sure if any specifically address linear models, but perhaps they provide enough of an example to get the gist:
- Benjamin Bolker has written a great book Ecological Data and Models with R. An early draft of the whole book along with Sweave code is available onlin... | null | CC BY-SA 2.5 | null | 2010-08-19T06:35:02.147 | 2010-08-19T06:35:02.147 | null | null | 183 | null |
1881 | 1 | 1901 | null | 16 | 6561 | I would like an advice on a analysis method I am using, to know if it it statistically sound.
I have measured two point processes $T^1 = t^1_1, t^1_2, ..., t^1_n$ and $T^2 = t^2_1, t^2_2, ..., t^2_m$ and I want to determine if the events in $T^1$ are somehow correlated to the events in $T^2$.
One of the methods that I ... | Analysis of cross correlation between point-processes | CC BY-SA 2.5 | null | 2010-08-19T06:42:15.767 | 2010-08-19T13:07:22.083 | null | null | 582 | [
"point-process",
"cross-correlation"
] |
1882 | 2 | null | 1829 | 82 | null | To answer the letter of the question, "ordinary least squares" is not an algorithm; rather it is a type of problem in computational linear algebra, of which linear regression is one example. Usually one has data $\{(x_1,y_1),\dots,(x_m,y_m)\}$ and a tentative function ("model") to fit the data against, of the form $f(x... | null | CC BY-SA 3.0 | null | 2010-08-19T06:42:28.403 | 2016-06-13T18:36:26.280 | 2016-06-13T18:36:26.280 | 830 | 830 | null |
1883 | 1 | null | null | 10 | 2075 | What areas of statistics have been substantially revolutionised in the last 50 years? For example, about 40 years ago, Akaike with colleagues revolutionised the area of statistical model discrimination. About 10 years ago, Hyndman with colleagues revolutionised the area of exponential smoothing. About XX years ago, ...... | Revolutions in statistics for the last 50 years? | CC BY-SA 3.0 | null | 2010-08-19T07:00:53.840 | 2015-11-22T13:36:21.940 | 2015-11-22T13:36:21.940 | 28666 | 273 | [
"history"
] |
1884 | 2 | null | 1865 | 2 | null | Suppose $X_n$ denotes the color of the $n$th card in the shuffled deck.
Then note that the last card always denotes the end of a run. Other ends of runs are characterized by $X_n\ne X_{n+1}$ which indicates a run ending at $n$.
Note that $P(X_n\ne X_{n+1})=26/51$ (since once you fix a card, you can choose another card ... | null | CC BY-SA 4.0 | null | 2010-08-19T08:34:51.493 | 2023-04-18T10:58:32.437 | 2023-04-18T10:58:32.437 | 362671 | 994 | null |
1885 | 2 | null | 1850 | 9 | null | To my understanding, Hedges's g is a somewhat more accurate version of Cohen's d (with pooled SD) in that we add a correction factor for small sample. Both measures generally agree when the homoscedasticity assumption is not violated, but we may found situations where this is not the case, see e.g. McGrath & Meyer, Psy... | null | CC BY-SA 4.0 | null | 2010-08-19T08:50:44.340 | 2020-11-03T20:02:33.500 | 2020-11-03T20:02:33.500 | 930 | 930 | null |
1887 | 2 | null | 10 | 48 | null | Maybe too late but I add my answer anyway...
It depends on what you intend to do with your data: If you are interested in showing that scores differ when considering different group of participants (gender, country, etc.), you may treat your scores as numeric values, provided they fulfill usual assumptions about varian... | null | CC BY-SA 3.0 | null | 2010-08-19T10:00:00.370 | 2012-07-11T11:04:18.083 | 2012-07-11T11:04:18.083 | 930 | 930 | null |
1888 | 2 | null | 203 | 13 | null | Clason & Dormody discussed the issue of statistical testing for Likert items ([Analyzing data measured by individual Likert-type items](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.113.2197&rep=rep1&type=pdf)). I think that a bootstrapped test is ok when the two distributions look similar (bell shaped and e... | null | CC BY-SA 3.0 | null | 2010-08-19T10:19:35.723 | 2014-12-15T03:53:44.170 | 2014-12-15T03:53:44.170 | 805 | 930 | null |
1889 | 2 | null | 1883 | 15 | null | Efron's work on the [Bootstrap](http://en.wikipedia.org/wiki/Bootstrapping_%28statistics%29) comes to mind.
| null | CC BY-SA 2.5 | null | 2010-08-19T10:29:27.773 | 2010-08-19T10:44:00.393 | 2010-08-19T10:44:00.393 | null | 334 | null |
1890 | 2 | null | 1883 | 4 | null | The creation of this site ;-)
| null | CC BY-SA 2.5 | null | 2010-08-19T10:45:32.653 | 2010-08-19T10:45:32.653 | null | null | null | null |
1891 | 2 | null | 1883 | 6 | null | Generalized linear models due to the recently deceased John Nelder and Robert Wedderburn.
| null | CC BY-SA 2.5 | null | 2010-08-19T11:03:39.603 | 2010-08-19T11:03:39.603 | null | null | 521 | null |
1892 | 2 | null | 1883 | 4 | null |
- Revolution 1: S (ACM Software Systems Award)
- Revolution 2: R (Ross Ihaka (1998) on the history of R to that point)
| null | CC BY-SA 2.5 | null | 2010-08-19T11:06:22.780 | 2010-08-19T11:06:22.780 | null | null | 183 | null |
1893 | 2 | null | 1883 | 15 | null | The application of Bayesian statistics with Monte Carlo methods.
| null | CC BY-SA 2.5 | null | 2010-08-19T11:21:55.827 | 2010-08-19T11:21:55.827 | null | null | 5 | null |
1894 | 2 | null | 1883 | 11 | null | [Ensemble methods](http://en.wikipedia.org/wiki/Ensemble_learning) like boosting, bagging, ... etc are another potential candidate.
| null | CC BY-SA 2.5 | null | 2010-08-19T11:22:51.240 | 2010-08-19T11:22:51.240 | null | null | 334 | null |
1895 | 1 | null | null | 4 | 1108 | I have a software benchmark which is quite noisy. I am trying to for the bugs which are causing the noise, and I need to be able to measure it somehow.
The benchmark is comprised of a number of subbenchmarks, for example:
```
"3d-cube": 31.56884765625,
"3d-morph": 21.89599609375,
"3d-raytrace": 51.802978515625,
"access... | Determining the "variability" of a benchmark | CC BY-SA 2.5 | null | 2010-08-19T11:33:01.067 | 2022-11-23T10:04:33.483 | 2017-12-14T08:55:25.773 | 1352 | 1001 | [
"variance"
] |
1896 | 2 | null | 1895 | 3 | null | I guess that your method is the one described [here](http://en.wikipedia.org/wiki/Absolute_deviation), and it's apparently valid. You could also have used the [standard deviation](http://en.wikipedia.org/wiki/Standard_deviation) as a measure of variability (which according to the article, it's not as [robust](http://en... | null | CC BY-SA 2.5 | null | 2010-08-19T11:58:09.057 | 2010-08-19T11:58:09.057 | null | null | 339 | null |
1897 | 2 | null | 1895 | 4 | null | As gd047 mentioned, the standard way of measuring variability is to use the [variance](http://en.wikipedia.org/wiki/Variance). So your pseudo-code will be:
```
vnew = vector of length subbenchmarks
for s in subbenchmarks:
vnew[i] = variance(s)
```
Now the problem is, even if you don't change your code, `vnew` will ... | null | CC BY-SA 4.0 | null | 2010-08-19T12:29:30.023 | 2022-11-23T10:04:33.483 | 2022-11-23T10:04:33.483 | 362671 | 8 | null |
1898 | 2 | null | 1883 | 5 | null | There was a great discussion on metaoptimize called "[Most Influential Ideas 1995 - 2005](http://metaoptimize.com/qa/questions/867/most-influential-ideas-1995-2005)"
Which holds a great collection of ideas.
The one I mentioned there, and will repeat here, is the "revolution" in the concept of multiple comparisons, spe... | null | CC BY-SA 2.5 | null | 2010-08-19T12:45:55.700 | 2010-08-19T12:45:55.700 | null | null | 253 | null |
1899 | 2 | null | 1883 | 4 | null | Cox proportional hazards survival analysis:
[http://en.wikipedia.org/wiki/Cox_proportional_hazards_model](http://en.wikipedia.org/wiki/Cox_proportional_hazards_model)
| null | CC BY-SA 2.5 | null | 2010-08-19T12:50:42.303 | 2010-08-19T12:50:42.303 | null | null | 521 | null |
1900 | 2 | null | 1883 | 9 | null | John Tukey's truly strange idea: exploratory data analysis.
[http://en.wikipedia.org/wiki/Exploratory_data_analysis](http://en.wikipedia.org/wiki/Exploratory_data_analysis)
| null | CC BY-SA 2.5 | null | 2010-08-19T13:01:46.790 | 2010-08-19T13:01:46.790 | null | null | 521 | null |
1901 | 2 | null | 1881 | 11 | null | A standard method to analyze this problem in two or more dimensions is Ripley's (cross) K function, but there's no reason not to use it in one dimension, too. (A Google search does a good job of digging up references.) Essentially, it plots the CDF of all distances between points in the two realizations rather than a... | null | CC BY-SA 2.5 | null | 2010-08-19T13:07:22.083 | 2010-08-19T13:07:22.083 | null | null | 919 | null |
1902 | 2 | null | 1883 | 4 | null | The Box-Jenkins approach to time-series modelling: ARIMA models etc.
[http://en.wikipedia.org/wiki/Box-Jenkins](http://en.wikipedia.org/wiki/Box-Jenkins)
| null | CC BY-SA 2.5 | null | 2010-08-19T13:09:50.597 | 2010-08-19T13:09:50.597 | null | null | 521 | null |
1903 | 2 | null | 1875 | 6 | null | In effect you are thinking of a model in which the true chance of rain, p, is a function of the predicted chance q: p = p(q). Each time a prediction is made, you observe one realization of a Bernoulli variate having probability p(q) of success. This is a classic logistic regression setup if you are willing to model t... | null | CC BY-SA 2.5 | null | 2010-08-19T13:21:56.153 | 2010-08-19T13:21:56.153 | null | null | 919 | null |
1904 | 1 | null | null | 14 | 1002 | What are the most significant annual Statistics conferences?
Rules:
- One conference per answer
- Include a link to the conference
| Statistics conferences? | CC BY-SA 2.5 | null | 2010-08-19T13:25:53.413 | 2022-12-15T06:46:10.637 | null | null | 5 | [
"conferences"
] |
1905 | 2 | null | 1904 | 3 | null | Shameless plug: [R/Finance](http://www.RinFinance.com) which relevant for its intersection of domain-specifics as well as tools, and so far well received by participants of the 2009 and 2010 conference. .
Disclaimer: I am one of the organizers.
| null | CC BY-SA 2.5 | null | 2010-08-19T13:30:01.783 | 2010-08-19T13:30:01.783 | null | null | 334 | null |
1906 | 1 | null | null | 8 | 597 | What are the most significant annual Data Mining conferences?
Rules:
- One conference per answer
- Include a link to the conference
| Data mining conferences? | CC BY-SA 2.5 | null | 2010-08-19T13:37:35.557 | 2022-12-04T11:14:04.433 | 2011-11-17T15:30:18.353 | 6976 | 5 | [
"data-mining",
"conferences"
] |
1907 | 2 | null | 1906 | 7 | null | [KDD](https://web.archive.org/web/20100701205656/http://www.sigkdd.org/conferences.php) (ACM Special Interest Group on Knowledge Discovery and Data Mining)
- KDD 2010
| null | CC BY-SA 4.0 | null | 2010-08-19T13:40:35.720 | 2022-12-04T11:06:28.573 | 2022-12-04T11:06:28.573 | 362671 | 5 | null |
1908 | 1 | null | null | 6 | 1809 | What are the most significant annual Machine Learning conferences?
Rules:
- One conference per answer
- Include a link to the conference
| Machine Learning conferences? | CC BY-SA 2.5 | null | 2010-08-19T13:45:36.037 | 2015-10-28T19:34:49.797 | 2010-08-23T15:27:33.560 | 877 | 5 | [
"machine-learning",
"conferences"
] |
1909 | 2 | null | 1904 | 7 | null | UseR!
- List of previous and upcoming R conferences on r-project
Related Links:
- 2011: University of Warwick, Coventry, UK
- Videos of some keynote speakers from 2010
| null | CC BY-SA 4.0 | null | 2010-08-19T13:46:41.337 | 2022-12-15T05:22:59.057 | 2022-12-15T05:22:59.057 | 362671 | 183 | null |
1910 | 2 | null | 1908 | 7 | null | [ICML](http://en.wikipedia.org/wiki/ICML) (International Conference on Machine Learning)
- ICML 2010
| null | CC BY-SA 2.5 | null | 2010-08-19T13:47:24.127 | 2010-08-19T13:47:24.127 | null | null | 5 | null |
1911 | 2 | null | 1883 | 10 | null | In 1960 most people doing statistics were calculating with a four-function manual calculator or a slide rule or by hand; mainframe computers were just beginning to run some programs in Algol and Fortran; graphical output devices were rare and crude. Because of these limitations, Bayesian analysis was considered formid... | null | CC BY-SA 2.5 | null | 2010-08-19T14:13:27.077 | 2010-08-19T14:13:27.077 | null | null | 919 | null |
1912 | 1 | 1959 | null | 4 | 374 | [Gary King](http://gking.harvard.edu/) made the [following statement on Twitter](http://twitter.com/kinggary/status/21513150698):
>
scale invariance sounds cool but is
usually statisticians shirking
responsibility & losing power by
neglecting subject matter info
What is an example of this phenomena, where [sca... | Why can scale invariance cause a loss of explanatory power? | CC BY-SA 2.5 | null | 2010-08-19T14:15:28.693 | 2010-08-27T15:21:05.230 | 2010-08-20T15:19:17.757 | 5 | 5 | [
"scale-invariance"
] |
1913 | 2 | null | 1904 | 5 | null | In terms of overall breadth, I would say that the ASA/IMS Joint Statistical Meetings are the most significant. Next year, the statisticians are taking their talents to South Beach...or [Miami Beach](http://www.amstat.org/meetings/jsm/2011/index.cfm) is more correct. I just couldn't help to use that line from Lebron J... | null | CC BY-SA 2.5 | null | 2010-08-19T14:38:51.867 | 2010-08-19T14:38:51.867 | null | null | null | null |
1914 | 1 | null | null | 5 | 410 | I doing spatial bayesian data analysis, I am assuming a no-nugget exponential covariance. I have tried a variety of priors for the sills and range parameters (gamma, inverse gamma etc.) , unfortunately the convergence diagonstics are typically horrible.
I am wondering how to figure out the poor mixing I observe, is th... | Choice for priors for exponential spatial covariance | CC BY-SA 2.5 | null | 2010-08-19T15:13:49.887 | 2010-09-18T22:00:39.013 | 2010-09-18T22:00:39.013 | 930 | 1004 | [
"bayesian",
"markov-chain-montecarlo",
"spatial"
] |
1915 | 1 | 1917 | null | 8 | 3855 | I am interested in running Newman's [modularity clustering](http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1482622/) algorithm on a large graph. If you can point me to a library (or R package, etc) that implements it I would be most grateful.
| Newman's modularity clustering for graphs | CC BY-SA 3.0 | null | 2010-08-19T16:09:23.430 | 2016-05-17T02:18:02.557 | 2016-05-17T02:18:02.557 | 114327 | 1007 | [
"clustering",
"networks",
"partitioning",
"igraph",
"modularity"
] |
1916 | 2 | null | 1914 | 3 | null | Diggle and Ribeiro discuss this in their book ("[Model-based Geostatistics](http://rads.stackoverflow.com/amzn/click/0387329072)"): see section 5.4.2. They quote some research suggesting that re-parameterization might help a little. For an exponential model (a Matern model with kappa = 1/2) this research suggests usi... | null | CC BY-SA 2.5 | null | 2010-08-19T16:31:49.917 | 2010-08-20T08:27:30.700 | 2010-08-20T08:27:30.700 | 8 | 919 | null |
1917 | 2 | null | 1915 | 6 | null | The [igraph](http://cran.r-project.org/web/packages/igraph/index.html) library implements some algorithms for community structure based on Newman's optimization of modularity. You can consult the [reference manual](http://cran.r-project.org/web/packages/igraph/igraph.pdf) for details and citations.
| null | CC BY-SA 2.5 | null | 2010-08-19T16:59:14.233 | 2010-08-19T16:59:14.233 | null | null | 251 | null |
1918 | 2 | null | 1866 | 4 | null | I'm not sure you need simulation for a simple regression model. For example, see the paper [Portable Power](http://www.jstor.org/stable/1267939), by Robert E. Wheeler (Technometrics , May, 1974, Vol. 16, No. 2). For more complex models, specifically mixed effects, the [pamm](http://cran.r-project.org/web/packages/pam... | null | CC BY-SA 4.0 | null | 2010-08-19T17:13:01.420 | 2021-08-19T18:16:33.700 | 2021-08-19T18:16:33.700 | 11887 | 251 | null |
1919 | 2 | null | 1904 | 0 | null | Not a "statistics" conference in the technical sense, but Predictive Analytics World is a case study conference on how companies are using predictive and other analytics in theis businesses.
[Predictive Analytics World](http://www.predictiveanalyticsworld.com/)
| null | CC BY-SA 2.5 | null | 2010-08-19T17:14:39.123 | 2010-08-19T17:14:39.123 | null | null | 11 | null |
1920 | 2 | null | 1904 | 0 | null | [ACM SIGKDD 2010](http://www.kdd.org/kdd2010/index.shtml)
[KDD 2011 in San Diego](http://kdd.org/kdd/2011/)
| null | CC BY-SA 2.5 | null | 2010-08-19T17:19:52.763 | 2010-08-19T17:19:52.763 | null | null | 11 | null |
1921 | 2 | null | 1863 | 4 | null | I just want to emphasize the importance of not analyzing accuracies on the proportion scale. While lamentably pervasive across a number of disciplines, this practice can yield frankly incorrect conclusions. See: [http://dx.doi.org/10.1016/j.jml.2007.11.004](http://dx.doi.org/10.1016/j.jml.2007.11.004)
As John Christie ... | null | CC BY-SA 2.5 | null | 2010-08-19T17:24:19.183 | 2010-08-19T17:43:34.613 | 2010-08-19T17:43:34.613 | 364 | 364 | null |
1922 | 2 | null | 1862 | 9 | null | There's a nice paper on visualization techniques you might use by Michael Friendly:
- Visualizing Categorical Data: Data, Stories, and Pictures
(Actually, there's a whole [book](http://books.google.com/books?id=eG0phz62f1cC&lpg=PP1&dq=michael%20friendly%20visualizing%20categorical%20data&pg=PP1#v=onepage&q&f=false) ... | null | CC BY-SA 2.5 | null | 2010-08-19T17:28:18.883 | 2010-08-19T17:28:18.883 | null | null | 251 | null |
1923 | 1 | 2509 | null | 6 | 513 | Suppose instead of maximizing likelihood I maximize some other function g. Like likelihood, this function decomposes over x's (ie, g({x1,x2})=g({x1})g({x2}), and "maximum-g" estimator is consistent. How do I compute asymptotic variance of this estimator?
Update 8/24/10: Percy Liang goes through derivation of asymptotic... | How to compute efficiency? | CC BY-SA 4.0 | null | 2010-08-19T17:56:58.550 | 2022-12-04T06:16:41.183 | 2022-12-04T06:16:41.183 | 362671 | 511 | [
"estimation",
"efficiency",
"asymptotics"
] |
1924 | 2 | null | 1923 | 2 | null | The consistency and asymptotic normality of the maximum likelihood estimator is demonstrated using some regularity conditions on the likelihood function. The wiki link on [consistency](http://en.wikipedia.org/wiki/Maximum_likelihood#Consistency) and [asymptotic normality](http://en.wikipedia.org/wiki/Maximum_likelihood... | null | CC BY-SA 2.5 | null | 2010-08-19T18:29:24.990 | 2010-08-19T18:29:24.990 | null | null | null | null |
1925 | 2 | null | 203 | 0 | null | Proportional odds ratio model is better then t-test for Likert item scale.
| null | CC BY-SA 2.5 | null | 2010-08-19T18:30:39.777 | 2010-08-19T18:30:39.777 | null | null | 419 | null |
1926 | 2 | null | 1904 | 5 | null | For biostatistics the largest US conferences are the meetings of the local sections of the International Biometrics Society (IBS):
- ENAR for the Eastern region
- WNAR for the Western region
Of these ENAR is by far larger.
| null | CC BY-SA 4.0 | null | 2010-08-19T18:43:16.163 | 2022-12-15T05:26:02.587 | 2022-12-15T05:26:02.587 | 362671 | 279 | null |
1927 | 1 | null | null | 38 | 6757 | If so, what?
If not, why not?
For a sample on the line, the median minimizes the total absolute deviation. It would seem natural to extend the definition to R2, etc., but I've never seen it. But then, I've been out in left field for a long time.
| Is there an accepted definition for the median of a sample on the plane, or higher ordered spaces? | CC BY-SA 2.5 | null | 2010-08-19T19:36:01.337 | 2022-08-06T19:09:10.103 | 2018-08-01T20:42:56.327 | 11887 | 1011 | [
"multivariate-analysis",
"spatial",
"median"
] |
1928 | 2 | null | 1927 | 21 | null | I'm not sure there is one accepted definition for a multivariate median. The one I'm familiar with is [Oja's median point](http://cgm.cs.mcgill.ca/~athens/Geometric-Estimators/oja.html), which minimizes the sum of volumes of simplices formed over subsets of points. (See the link for a technical definition.)
Update: T... | null | CC BY-SA 2.5 | null | 2010-08-19T19:48:16.567 | 2010-08-19T19:58:31.783 | 2010-08-19T19:58:31.783 | 251 | 251 | null |
1929 | 2 | null | 1927 | 1 | null | I do not know if any such definition exists but I will try and extend the [standard definition of the median](http://en.wikipedia.org/wiki/Median#An_optimality_property) to $R^2$. I will use the following notation:
$X$, $Y$: the random variables associated with the two dimensions.
$m_x$, $m_y$: the corresponding median... | null | CC BY-SA 2.5 | null | 2010-08-19T19:53:51.467 | 2010-08-19T19:53:51.467 | null | null | null | null |
1930 | 2 | null | 1850 | 25 | null | Both Cohen's d and Hedges' g pool variances on the assumption of equal population variances, but g pools using n - 1 for each sample instead of n, which provides a better estimate, especially the smaller the sample sizes. Both d and g are somewhat positively biased, but only negligibly for moderate or larger sample si... | null | CC BY-SA 2.5 | null | 2010-08-19T20:52:10.220 | 2010-08-19T20:52:10.220 | null | null | 1013 | null |
1931 | 2 | null | 1927 | 12 | null | There are distinct ways to generalize the concept of median to higher dimensions. One not yet mentioned, but which was proposed long ago, is to construct a convex hull, peel it away, and iterate for as long as you can: what's left in the last hull is a set of points that are all candidates to be "medians."
["Head-bang... | null | CC BY-SA 3.0 | null | 2010-08-19T20:58:59.157 | 2015-02-11T14:37:28.947 | 2015-02-11T14:37:28.947 | 919 | 919 | null |
1932 | 2 | null | 1908 | 7 | null | [NIPS (Neural Information Processing Systems)](http://nips.cc). It's actually an intersection of machine learning, and application areas such as speech/language, vision, neuro-science, and other related areas.
| null | CC BY-SA 2.5 | null | 2010-08-19T21:44:04.807 | 2010-08-19T21:44:04.807 | null | null | 881 | null |
1933 | 2 | null | 1826 | 3 | null | Since you don't have access to the test data at the time of training, and you want your model to do well on the unseen test data, you "pretend" that you have access to some test data by repeatedly subsampling a small part of your training data, hold out this set while training the model, and then treating the held out ... | null | CC BY-SA 2.5 | null | 2010-08-19T21:50:48.220 | 2010-08-19T23:49:54.203 | 2010-08-19T23:49:54.203 | 881 | 881 | null |
1934 | 2 | null | 1228 | 3 | null | Thomas Ryan ("Statistical Methods for Quality Improvement", Wiley, 1989) describes several procedures. He tends to try to reduce all control charting to the Normal case, so his procedures are not as creative as they could be, but he claims they work pretty well. One is to treat the values as Binomial data and use the... | null | CC BY-SA 2.5 | null | 2010-08-19T22:08:44.573 | 2010-08-19T22:08:44.573 | null | null | 919 | null |
1935 | 1 | null | null | 9 | 2088 | Despite several attempts at reading about bootstrapping, I seem to always hit a brick wall. I wonder if anyone can give a reasonably non-technical definition of bootstrapping?
I know it is not possible in this forum to provide enough detail to enable me to fully understand it, but a gentle push in the right direction w... | Whither bootstrapping - can someone provide a simple explanation to get me started? | CC BY-SA 2.5 | null | 2010-08-20T00:10:33.740 | 2017-06-26T12:19:21.890 | 2017-06-26T12:19:21.890 | 11887 | 561 | [
"nonparametric",
"bootstrap",
"intuition"
] |
1936 | 2 | null | 1908 | 0 | null | One of the only machine learning conferences for those in Australia and New Zealand is:
- 23rd Australasian Joint Conference on Artificial Intelligence
It's held in Adelaide this year.
| null | CC BY-SA 2.5 | null | 2010-08-20T00:16:09.237 | 2010-08-20T00:16:09.237 | null | null | 530 | null |
1937 | 2 | null | 1935 | 4 | null | The wiki on [bootstrapping](http://en.wikipedia.org/wiki/Bootstrapping_%28statistics%29) gives the following description:
>
Bootstrapping allows one to gather many alternative versions of the single statistic that would ordinarily be calculated from one sample. For example, assume we are interested in the height of pe... | null | CC BY-SA 2.5 | null | 2010-08-20T00:20:49.803 | 2010-08-20T00:20:49.803 | null | null | null | null |
1938 | 2 | null | 1904 | 2 | null | The main regular conference in Australia is the "Australian Statistics Conference", held every second year. The next one is [ASC 2010](http://www.promaco.com.au/2010/asc/), to be held in Western Australia in December.
| null | CC BY-SA 2.5 | null | 2010-08-20T00:23:03.980 | 2010-08-20T00:23:03.980 | null | null | 159 | null |
1939 | 2 | null | 1935 | 8 | null | The Wikipedia entry on Bootstrapping is actually very good:
[http://en.wikipedia.org/wiki/Bootstrapping_%28statistics%29](http://en.wikipedia.org/wiki/Bootstrapping_%28statistics%29)
The most common reason bootstrapping is applied is when the form of the underlying distribution from which a sample is taken is unknown. ... | null | CC BY-SA 2.5 | null | 2010-08-20T00:35:28.433 | 2010-08-20T00:35:28.433 | null | null | 521 | null |
1940 | 2 | null | 1935 | 8 | null | The American Scientist recently had a nice article by Cosma Shalizi on [the bootstrap](http://www.americanscientist.org/issues/pub/2010/3/the-bootstrap/1) which is fairly easy reading and gives you the essentials to grasp the concept.
| null | CC BY-SA 2.5 | null | 2010-08-20T01:08:12.280 | 2010-08-20T01:08:12.280 | null | null | 251 | null |
1941 | 2 | null | 1781 | 5 | null | I have not full internalized the issue of matrix interference but here is one approach. Let:
$Y$ be a vector that represents the concentration of all the target compounds in the undiluted sample.
$Z$ be the corresponding vector in the diluted sample.
$d$ be the dilution factor i.e., the sample is diluted $d$:1.
Our mod... | null | CC BY-SA 2.5 | null | 2010-08-20T01:47:20.863 | 2010-08-20T01:47:20.863 | null | null | null | null |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.