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7347 | 2 | null | 7330 | 1 | null | Yes, arbitrary rotations in an $n$ dimensional space can be written as the compositions of Givens rotations. The other question (and I think what you're aiming at) is
>
Or perhaps a better question is: if a
prior distribution is invariant when
rotated about 2 arbitrary dimensions,
is it invariant when rotated ab... | null | CC BY-SA 2.5 | null | 2011-02-17T22:00:09.717 | 2011-02-17T22:00:09.717 | null | null | 30 | null |
7348 | 1 | 7349 | null | 35 | 24598 | I find R can take a long time to generate plots when millions of points are present - unsurprising given that points are plotted individually. Furthermore, such plots are often too cluttered and dense to be useful. Many of the points overlap and form a black mass and a lot of time is spent plotting more points into tha... | Statistical methods to more efficiently plot data when millions of points are present? | CC BY-SA 4.0 | null | 2011-02-17T22:29:30.310 | 2019-11-14T10:45:29.190 | 2018-06-27T21:45:14.067 | 8013 | 2726 | [
"r",
"data-visualization"
] |
7349 | 2 | null | 7348 | 14 | null | This is a hard task with no ready solutions (this is of course because density plot is so a tempting fallback than no one really cares). So, what can you do?
If they really overlap (i.e. have exactly the same X & Y coordinates) and you are not using alpha, the best idea would be just to reduce the overlap using `unique... | null | CC BY-SA 2.5 | null | 2011-02-17T23:32:55.593 | 2011-02-17T23:32:55.593 | null | null | null | null |
7350 | 2 | null | 7 | 1 | null | [http://www.ckan.net](http://www.ckan.net) has a number of datasets too.
[http://www.biotorrents.net/browse.php](http://www.biotorrents.net/browse.php) is also starting to have quite a large amount of BIG datasets.
| null | CC BY-SA 2.5 | null | 2011-02-18T00:06:24.633 | 2011-02-18T00:06:24.633 | null | null | 3291 | null |
7351 | 1 | 7352 | null | 48 | 7976 | I am trying to get upto speed in Bayesian Statistics. I have a little bit of stats background (STAT 101) but not too much - I think I can understand prior, posterior, and likelihood :D.
I don't want to read a Bayesian textbook just yet.
I'd prefer to read from a source (website preferred) that will ramp me up quickly.... | Bayesian statistics tutorial | CC BY-SA 2.5 | null | 2011-02-18T00:35:17.267 | 2022-07-16T16:57:20.707 | 2012-10-16T16:16:40.557 | null | 3301 | [
"bayesian",
"references"
] |
7352 | 2 | null | 7351 | 19 | null | Here's a place to start:
[ftp://selab.janelia.org/pub/publications/Eddy-ATG3/Eddy-ATG3-reprint.pdf](ftp://selab.janelia.org/pub/publications/Eddy-ATG3/Eddy-ATG3-reprint.pdf)
[http://blog.oscarbonilla.com/2009/05/visualizing-bayes-theorem/](http://blog.oscarbonilla.com/2009/05/visualizing-bayes-theorem/)
[http://yudkows... | null | CC BY-SA 3.0 | null | 2011-02-18T01:04:21.207 | 2011-06-23T20:29:50.033 | 2011-06-23T20:29:50.033 | 2775 | 2775 | null |
7353 | 2 | null | 7348 | 17 | null | I must admit that I do not fully understand your last paragraph:
>
"I am not looking for a density plot
(although those are often useful), I
would want the same output as a simple
plot call but much faster than
millions of overplots if possible."
It is also unclear what type of plot (function) you are lookin... | null | CC BY-SA 3.0 | null | 2011-02-18T01:13:27.283 | 2016-01-13T18:52:38.197 | 2016-01-13T18:52:38.197 | 36419 | 307 | null |
7354 | 2 | null | 7208 | 4 | null | I find caracal's answer convincing, but I also believe Cohen's Kappa can only account for part of what constitutes interrater reliability. The simple % of ratings in agreement accounts for another part, and the correlation between ratings, a third. It takes all three methods to gain a complete picture. For details p... | null | CC BY-SA 2.5 | null | 2011-02-18T01:26:44.263 | 2011-02-18T01:26:44.263 | null | null | 2669 | null |
7355 | 2 | null | 7351 | 5 | null | Some more depth:
- http://math.tut.fi/~piche/bayes/notes01.pdf covers Bayes' theorem
- https://ccrma.stanford.edu/~jos/bayes/bayes.pdf and
- http://www-personal.une.edu.au/~jvanderw/Introduction_to_Bayesian_Statistics1.pdf are more about statistical applications
| null | CC BY-SA 2.5 | null | 2011-02-18T01:33:51.137 | 2011-02-18T01:33:51.137 | null | null | 2958 | null |
7356 | 2 | null | 7348 | 45 | null | Look at the [hexbin](http://cran.r-project.org/package=hexbin) package which implements paper/method by Dan Carr. The [pdf vignette](http://cran.r-project.org/web/packages/hexbin/vignettes/hexagon_binning.pdf) has more details which I quote below:
>
1 Overview
Hexagon binning is a form of bivariate
histogram useful ... | null | CC BY-SA 2.5 | null | 2011-02-18T02:02:39.183 | 2011-02-18T02:02:39.183 | null | null | 334 | null |
7357 | 1 | 7359 | null | 44 | 21328 | I know this is a fairly specific `R` question, but I may be thinking about proportion variance explained, $R^2$, incorrectly. Here goes.
I'm trying to use the `R` package `randomForest`. I have some training data and testing data. When I fit a random forest model, the `randomForest` function allows you to input new tes... | Manually calculated $R^2$ doesn't match up with randomForest() $R^2$ for testing new data | CC BY-SA 3.0 | null | 2011-02-18T02:32:48.823 | 2018-01-09T09:06:16.900 | 2018-01-09T09:06:16.900 | 128677 | 36 | [
"r",
"correlation",
"predictive-models",
"random-forest",
"r-squared"
] |
7358 | 1 | 7377 | null | 23 | 12515 | I've got a particular MCMC algorithm which I would like to port to C/C++. Much of the expensive computation is in C already via Cython, but I want to have the whole sampler written in a compiled language so that I can just write wrappers for Python/R/Matlab/whatever.
After poking around I'm leaning towards C++. A coupl... | C++ libraries for statistical computing | CC BY-SA 2.5 | null | 2011-02-18T02:40:12.390 | 2017-11-22T14:23:28.570 | 2017-11-22T14:23:28.570 | 11887 | 26 | [
"markov-chain-montecarlo",
"software",
"c++",
"computational-statistics"
] |
7359 | 2 | null | 7357 | 66 | null | The reason that the $R^2$ values are not matching is because `randomForest` is reporting variation explained as opposed to variance explained. I think this is a common misunderstanding about $R^2$ that is perpetuated in textbooks. I even mentioned this on another thread the other day. If you want an example, see the (o... | null | CC BY-SA 2.5 | null | 2011-02-18T03:31:08.217 | 2011-02-18T04:21:19.807 | 2011-02-18T04:21:19.807 | 2970 | 2970 | null |
7360 | 2 | null | 7358 | 1 | null | There are numerous C/C++ libraries out there, most focusing on a particular problem domain of (e.g. PDE solvers). There are two comprehensive libraries I can think of that you may find especially useful because they are written in C but have excellent Python wrappers already written.
1) [IMSL C](http://www.roguewave.co... | null | CC BY-SA 2.5 | null | 2011-02-18T04:08:36.080 | 2011-02-19T02:40:37.700 | 2011-02-19T02:40:37.700 | 1080 | 1080 | null |
7361 | 2 | null | 7358 | 7 | null | Boost Random from the Boost C++ libraries could be a good fit for you. In addition to many types of RNGs, it offers a variety of different distributions to draw from, such as
- Uniform (real)
- Uniform (unit sphere or arbitrary dimension)
- Bernoulli
- Binomial
- Cauchy
- Gamma
- Poisson
- Geometric
- Triangle... | null | CC BY-SA 2.5 | null | 2011-02-18T04:25:52.087 | 2011-02-18T04:25:52.087 | null | null | 1537 | null |
7362 | 1 | 7368 | null | 3 | 4082 | In Orwin's fail safe N test how to decide the values of criterion for a trivial log odd's ratio and mean log odds ratio in missing studies. I am a medical doctor. Please tell me in simple english.
The data are
```
1. Classic fail-safe N
Z-value for observed studies 27.97543
P-value f... | Orwin's fail safe N test | CC BY-SA 2.5 | null | 2011-02-18T05:58:42.340 | 2011-02-18T10:01:57.817 | 2011-02-18T09:45:21.120 | 307 | 2956 | [
"meta-analysis",
"publication-bias"
] |
7363 | 2 | null | 7326 | 0 | null | I believe a chi-squared test is what you are looking for. Because your dataset has a long tail, many tags will not be sampled well or will not end up in your sample at all. You may want to look into Yates' chi-square test, which attempts to correct for this by loosening the standards of what is significant for rare tag... | null | CC BY-SA 2.5 | null | 2011-02-18T06:07:14.057 | 2011-02-18T06:07:14.057 | null | null | 2965 | null |
7364 | 1 | null | null | 4 | 125 | The standard factor model formulation is
$y=W x+\epsilon$
where $x \sim \mathcal{N}(0, I)$, $\epsilon \sim\mathcal{N}(0, \Sigma)$. $W$ and $\Sigma$ are typically estimated from MLE. The solution can be obtained numerically; in general there are no analytical solutions.
Question: assume that $\Sigma$ belongs to some cla... | Factor models with small noises | CC BY-SA 2.5 | null | 2011-02-18T06:10:01.733 | 2011-02-18T06:10:01.733 | null | null | 30 | [
"factor-analysis",
"maximum-likelihood",
"asymptotics"
] |
7365 | 2 | null | 7308 | 7 | null | The quotation in full [can be found here](http://books.google.com/books?id=cdBPOJUP4VsC&lpg=PP1&dq=wooldridge%20econometrics&hl=fr&pg=PA357#v=onepage&q=wooldridge%20econometrics&f=false). The estimate $\hat{\theta}_N$ is the solution of minimization problem ([page 344](http://books.google.com/books?id=cdBPOJUP4VsC&lpg=... | null | CC BY-SA 2.5 | null | 2011-02-18T08:56:34.040 | 2011-02-25T11:23:38.733 | 2011-02-25T11:23:38.733 | 2116 | 2116 | null |
7366 | 1 | 7373 | null | 2 | 2311 | I am a beginner in statistics, therefore I hope I can state my problem in a correct manner. I have a some instances or samples and I can collect below statistical parameters for classification and regression problem:
- Sample Size
- Minimum value
- Maximum value
- Standard deviation
- Variance
- Mean
And, I wan... | Is z-score meaningful in classification or regression? | CC BY-SA 2.5 | null | 2011-02-18T09:09:36.343 | 2011-02-18T11:08:11.973 | 2011-02-18T10:05:42.170 | 930 | 2170 | [
"classification",
"z-statistic"
] |
7367 | 2 | null | 7358 | 9 | null | I would strongly suggest that you have a look at `RCpp` and `RcppArmadillo` packages for `R`. Basically, you would not need to worry about the wrappers as they are already "included". Furthermore the syntactic sugar is really sweet (pun intended).
As a side remark, I would recommend that you have a look at `JAGS`, whic... | null | CC BY-SA 2.5 | null | 2011-02-18T09:32:00.917 | 2011-02-18T09:32:00.917 | null | null | 1443 | null |
7368 | 2 | null | 7362 | 6 | null | The criterion for a 'trivial' effect size (odds ratio in your example) should be decided based on the size of effect that would be considered 'trivial' in the particular scenario, rather than on statistical grounds. If you're looking at an intervention that may be given to a considerable segment of the population with ... | null | CC BY-SA 2.5 | null | 2011-02-18T10:01:57.817 | 2011-02-18T10:01:57.817 | null | null | 449 | null |
7369 | 2 | null | 7344 | 4 | null | In addition to @mpiktas's comment, you can also have a look at the [rms](http://cran.r-project.org/web/packages/rms/index.html) package from Frank Harrell. The advantage is that it handles both LM and GLM for model fitting and prediction; see for example the `plot.Predict()` function. If you're planning to do serious j... | null | CC BY-SA 2.5 | null | 2011-02-18T10:04:53.950 | 2011-02-18T10:04:53.950 | null | null | 930 | null |
7370 | 1 | 7372 | null | 2 | 136 | I would like to check different gradient algorithms. For example:
```
fr <- function(x) { ## Rosenbrock Banana function
x1 <- x[1]
x2 <- x[2]
print(c(x1,x2))
100 * (x2 - x1 * x1)^2 + (1 - x1)^2
}
optim(c(-1.2,1),fr,method="BFGS")
```
prints to the screen the values at which t... | How to store checks of gradient algorithm in a matrix using R? | CC BY-SA 2.5 | null | 2011-02-18T10:21:17.707 | 2016-03-04T12:19:38.220 | 2016-03-04T12:19:38.220 | 603 | 603 | [
"r"
] |
7372 | 2 | null | 7370 | 4 | null | Use the function capture.output:
```
cc<-capture.output(vv<-optim(c(-1.2,1),fr,method="BFGS"))
t(sapply(strsplit(gsub(" +"," ",cc)," "),function(l)as.numeric(l[2:3])))
```
The variable `vv` is used so that the result of optim will not be printed only your calls to the function. Each call to the function results in one... | null | CC BY-SA 2.5 | null | 2011-02-18T11:00:21.777 | 2011-02-19T06:50:00.900 | 2011-02-19T06:50:00.900 | 2116 | 2116 | null |
7373 | 2 | null | 7366 | 3 | null | In order to perform linear regression you'd need not only the means and variances of the variables but also all their covariances (or equivalently their correlations).
If you can collect the means, variances and covariances/correlations separately in each of the classes you wish to classify, you can do [linear discrim... | null | CC BY-SA 2.5 | null | 2011-02-18T11:08:11.973 | 2011-02-18T11:08:11.973 | null | null | 449 | null |
7374 | 2 | null | 7351 | 2 | null | You could try '[Teaching Bayesian Reasoning In Less Than Two Hours](https://www.apa.org/pubs/journals/releases/xge-1303380.pdf)'.
| null | CC BY-SA 3.0 | null | 2011-02-18T12:10:29.613 | 2016-06-27T06:44:41.230 | 2016-06-27T06:44:41.230 | 22 | 22 | null |
7375 | 2 | null | 7351 | 8 | null | If you'd like to try a few learn by examples, you may be interested in "[Bayesian Computation in R](http://bayes.bgsu.edu/bcwr/)" by Jim Albert.
Its related R package is called LearnBayes.
| null | CC BY-SA 3.0 | null | 2011-02-18T12:59:46.510 | 2012-05-15T07:17:04.137 | 2012-05-15T07:17:04.137 | 582 | 3306 | null |
7376 | 1 | 7378 | null | 30 | 18639 | Inter-market analysis is a method of modeling market behavior by means of finding relationships between different markets. Often times, a correlation is computed between two markets, say S&P 500 and 30-Year US treasuries. These computations are more often than not based on price data, which is obvious to everyone that ... | Does correlation assume stationarity of data? | CC BY-SA 2.5 | null | 2011-02-18T13:07:06.643 | 2016-08-05T18:06:20.690 | null | null | 3306 | [
"correlation",
"stationarity"
] |
7377 | 2 | null | 7358 | 18 | null | We have spent some time making the wrapping from C++ into [R](http://www.r-project.org) (and back for that matter) a lot easier via our [Rcpp](http://dirk.eddelbuettel.com/code/rcpp.html) package.
And because linear algebra is already such a well-understood and coded-for field, [Armadillo](http://arma.sf.net), a curr... | null | CC BY-SA 2.5 | null | 2011-02-18T15:41:38.457 | 2011-02-18T16:39:18.800 | 2011-02-18T16:39:18.800 | 334 | 334 | null |
7378 | 2 | null | 7376 | 42 | null | The correlation measures linear relationship. In informal context relationship means something stable. When we calculate the sample correlation for stationary variables and increase the number of available data points this sample correlation tends to true correlation.
It can be shown that for prices, which usually ar... | null | CC BY-SA 3.0 | null | 2011-02-18T15:46:08.050 | 2016-08-05T18:06:20.690 | 2016-08-05T18:06:20.690 | 31363 | 2116 | null |
7379 | 1 | 14670 | null | 4 | 195 | I'm reading through someone else's code for plotting the results of a psychology experiment, and (according to the code comments) they calculate the accuracy error of their behavioral paradigm as follows:
$\textit{accuracy error} = \sqrt{\frac{(\textit{accuracy}) (1-\textit{accuracy})}{\textit{total trials}}}$
It's out... | What is this measure of error? | CC BY-SA 2.5 | null | 2011-02-18T16:40:42.403 | 2011-08-23T00:38:20.873 | 2011-02-18T16:54:52.120 | 919 | 2019 | [
"binomial-distribution",
"error"
] |
7380 | 5 | null | null | 0 | null | Econometrics is a field of statistics dealing with applications to economics.
For econometrics resources, refer to the following questions:
- Free econometrics textbooks
- Introductory statistics and econometrics in R
- Good econometrics textbooks?
| null | CC BY-SA 3.0 | null | 2011-02-18T17:52:05.987 | 2013-09-02T13:46:59.017 | 2013-09-02T13:46:59.017 | 27581 | 2116 | null |
7381 | 4 | null | null | 0 | null | Econometrics is a field of statistics dealing with applications to economics. | null | CC BY-SA 2.5 | null | 2011-02-18T17:52:05.987 | 2011-02-18T20:29:10.600 | 2011-02-18T20:29:10.600 | 2116 | 2116 | null |
7382 | 2 | null | 7376 | 14 | null | >
...is the computation of correlation whose data is non-stationary even a valid statistical calculation?
Let $W$ be a discrete random walk. Pick a positive number $h$. Define the processes $P$ and $V$ by $P(0) = 1$, $P(t+1) = -P(t)$ if $V(t) > h$, and otherwise $P(t+1) = P(t)$; and $V(t) = P(t)W(t)$. In other w... | null | CC BY-SA 2.5 | null | 2011-02-18T19:18:50.377 | 2011-02-18T19:18:50.377 | null | null | 919 | null |
7383 | 2 | null | 4762 | 1 | null | To use SPSS for the Lack of fit test go to: Analyze>>Compare Means>>Means.
Then in the dialogue box that appears assign your Independent and Dependent Variables. Select Options and a new dialogue box will appear. Check the option at the bottom of the screen that says "Test for Linearity".
| null | CC BY-SA 2.5 | null | 2011-02-18T20:40:13.133 | 2011-02-18T20:40:13.133 | null | null | null | null |
7384 | 2 | null | 7268 | 6 | null | Aggregation also works without using `zoo` (with random data from 2 variables for 3 days and 4 hosts like from JWM). I assume that you have data from all hosts for each hour.
```
nHosts <- 4 # number of hosts
dates <- seq(as.POSIXct("2011-01-01 00:00:00"),
as.POSIXct("2011-01-03 23:59:30"), by=30)
hosts... | null | CC BY-SA 2.5 | null | 2011-02-18T20:53:58.767 | 2011-02-18T21:03:34.373 | 2011-02-18T21:03:34.373 | 1909 | 1909 | null |
7385 | 1 | 7418 | null | 14 | 5082 | this is my first post. I'm truly grateful for this community.
I am trying to analyze longitudinal count data that is zero-truncated (probability that response variable = 0 is 0), and the mean != variance, so a negative binomial distribution was chosen over a poisson.
Functions/commands I've ruled out:
R
- gee() functi... | R/Stata package for zero-truncated negative binomial GEE? | CC BY-SA 2.5 | null | 2011-02-18T21:20:51.227 | 2013-08-13T14:53:07.500 | 2011-02-19T03:52:51.513 | 3309 | 3309 | [
"r",
"stata",
"count-data",
"panel-data",
"truncation"
] |
7386 | 6 | null | null | 0 | null | I am reluctant to make this nomination because I have been happy with the moderators. I would be delighted to see them continue in their roles.
However, to date only two people have entered nominations. (Is everyone else waiting until just before the deadline?) As you might guess from my activity here, I value this f... | null | CC BY-SA 2.5 | null | 2011-02-18T22:29:42.007 | 2011-02-18T22:29:42.007 | 2011-02-18T22:29:42.007 | 919 | 919 | null |
7387 | 2 | null | 7202 | 2 | null | Mixed models are usually used to take account of the correlation structure likely with a model like this. Look up Analyze>Mixed Models (MIXED) or the newer Mixed Models>Generalized Linear if you have the latest version.
HTH,
Jon Peck
| null | CC BY-SA 2.5 | null | 2011-02-18T22:55:09.213 | 2011-02-18T22:55:09.213 | null | null | null | null |
7389 | 1 | 7649 | null | 8 | 2223 | My question deals with how to be able to assert that an "improved"
evolutionary algorithm is indeed improved (at least from a statistic
point of view) and not just random luck (a concern given the
stochastic nature of these algorithms).
Let's assume I am dealing with a standard GA (before) and an "improved"
GA (after).... | How to check if modified genetic algorithm is significantly better than the original? | CC BY-SA 2.5 | null | 2011-02-18T23:34:23.113 | 2014-02-05T20:13:19.270 | 2011-02-20T23:52:35.640 | null | 10633 | [
"t-test",
"genetic-algorithms",
"multiple-comparisons"
] |
7391 | 1 | 35542 | null | 6 | 353 | I have seen asserted that the problem of computing the null distribution of Kolmogorov's $D_n^+$ statistic for a finite sample size maps onto the problem of computing the number of lattice paths that stay below the diagonal, and thus can be solved by the [ballot theorem](http://en.wikipedia.org/wiki/Bertrand%27s_ballot... | Kolmogorov-Smirnov and lattice paths | CC BY-SA 2.5 | null | 2011-02-19T01:57:52.283 | 2023-01-03T18:35:41.610 | 2012-09-01T22:54:53.643 | 8413 | 21874 | [
"kolmogorov-smirnov-test"
] |
7392 | 2 | null | 7385 | 9 | null | Hmm, good first question! I don't know of a package that meets your precise requirements. I think Stata's [xtgee](http://www.stata.com/help.cgi?xtgee) is a good choice if you also specify the `vce(robust)` option to give Huber-White standard errors, or `vce(bootstrap)` if that's practical. Either of these options will ... | null | CC BY-SA 2.5 | null | 2011-02-19T10:01:05.533 | 2011-02-19T10:01:05.533 | null | null | 449 | null |
7393 | 2 | null | 7389 | 4 | null | It might not be what you want to hear, but from what I've seen the new algorithm is just compared to the old one on benchmark functions.
E.g. as done here: [Efficient Natural Evolution Strategies, (Schaul, Sun Yi, Wierstra, Schmidhuber)](http://www.idsia.ch/~tom/publications/enes.pdf)
| null | CC BY-SA 2.5 | null | 2011-02-19T10:03:01.937 | 2011-02-19T13:02:11.847 | 2011-02-19T13:02:11.847 | 2860 | 2860 | null |
7394 | 1 | 7395 | null | 6 | 8465 | I have searched a lot, and I can only find tables that show critical values up to n=30. Can someone provide, or point me to, a simple method of estimating this value for different $\alpha$?
| How to estimate a critical value of Spearman's correlation for n=100? | CC BY-SA 2.5 | null | 2011-02-19T18:41:52.773 | 2011-02-19T19:16:55.457 | null | null | 977 | [
"hypothesis-testing",
"correlation",
"spearman-rho"
] |
7395 | 2 | null | 7394 | 3 | null | For values over thirty the approximation (for a two-tailed test) is
$$\frac{\Phi^{-1}\left(1-\tfrac{\alpha}{2}\right)}{\sqrt{n-1}}$$
so for example with $\alpha = 0.05$ and $n=100$ the numerator is about 1.96 and the denominator about 9.95, giving a critical value of about 0.197.
This comes from $\rho$ having approxim... | null | CC BY-SA 2.5 | null | 2011-02-19T19:08:00.543 | 2011-02-19T19:16:17.797 | 2011-02-19T19:16:17.797 | 2958 | 2958 | null |
7396 | 2 | null | 7394 | 7 | null | See Wikipedia: [Spearman's rank correlation coefficient#Determining significance](http://en.wikipedia.org/wiki/Spearman%27s_rank_correlation_coefficient#Determining_significance):
"One can test for significance using
$$t = r \sqrt{\frac{n-2}{1-r^2}},$$
which is distributed approximately as Student's $t$ distribution wi... | null | CC BY-SA 2.5 | null | 2011-02-19T19:16:55.457 | 2011-02-19T19:16:55.457 | null | null | 449 | null |
7397 | 2 | null | 363 | 4 | null |
- Michael Oakes' Statistical Inference: A Commentary for the Social and Behavioral Sciences.
- Elazar Pedhazur's Multiple Regression in Behavioral Research. If you can stand the immense detail and the self-important tone.
In case you're interested, I've reviewed both on Amazon and at [https://yellowbrickstats.com... | null | CC BY-SA 4.0 | null | 2011-02-19T19:25:19.687 | 2021-03-11T13:59:49.813 | 2021-03-11T13:59:49.813 | 2669 | 2669 | null |
7398 | 2 | null | 363 | 3 | null | Rice: [Mathematical Statistics and Data Analysis](http://goo.gl/wKbcW)
| null | CC BY-SA 2.5 | null | 2011-02-19T19:47:16.733 | 2011-02-19T19:47:16.733 | null | null | 609 | null |
7399 | 6 | null | null | 0 | null | I am nominating myself in part because of friendly pressure and because election is really election when there are more candidates than places to be filled.
I came to this site nearly three months ago and became instantly hooked. Moderating would not take a lot out of me, since I am already visiting the site daily, re... | null | CC BY-SA 2.5 | null | 2011-02-19T19:49:46.760 | 2011-02-19T19:49:46.760 | 2011-02-19T19:49:46.760 | 2116 | 2116 | null |
7400 | 1 | 7405 | null | 53 | 81362 | Given two histograms, how do we assess whether they are similar or not?
Is it sufficient to simply look at the two histograms?
The simple one to one mapping has the problem that if a histogram is slightly different and slightly shifted then we'll not get the desired result.
Any suggestions?
| How to assess the similarity of two histograms? | CC BY-SA 2.5 | null | 2011-02-19T18:52:26.557 | 2021-05-11T15:45:42.833 | 2011-02-21T06:40:35.937 | 183 | 3325 | [
"histogram",
"image-processing"
] |
7401 | 2 | null | 7400 | 11 | null | You're looking for the [Kolmogorov-Smirnov test](http://en.wikipedia.org/wiki/Kolmogorov%E2%80%93Smirnov_test). Don't forget to divide the bar heights by the sum of all observations of each histogram.
Note that the KS-test is also reporting a difference if e.g. the means of the distributions are shifted relative to one... | null | CC BY-SA 2.5 | null | 2011-02-19T19:22:04.820 | 2011-02-19T20:09:43.253 | null | null | 198 | null |
7402 | 1 | 7404 | null | 14 | 48821 | I know that a Type II error is where H1 is true, but H0 is not rejected.
### Question
How do I calculate the probability of a Type II error involving a normal distribution, where the standard deviation is known?
| How do I find the probability of a type II error? | CC BY-SA 2.5 | null | 2011-02-19T20:56:08.153 | 2018-11-19T08:55:24.940 | 2011-02-21T05:55:26.353 | 183 | null | [
"probability",
"statistical-power",
"type-i-and-ii-errors"
] |
7404 | 2 | null | 7402 | 32 | null | In addition to specifying $\alpha$ (probability of a type I error), you need a fully specified hypothesis pair, i.e., $\mu_{0}$, $\mu_{1}$ and $\sigma$ need to be known. $\beta$ (probability of type II error) is $1 - \textrm{power}$. I assume a one-sided $H_{1}: \mu_{1} > \mu_{0}$. In R:
```
> sigma <- 15 # theoreti... | null | CC BY-SA 4.0 | null | 2011-02-19T21:13:06.140 | 2018-11-19T08:55:24.940 | 2018-11-19T08:55:24.940 | 1909 | 1909 | null |
7405 | 2 | null | 7400 | 11 | null | A recent paper that may be worth reading is:
[Cao, Y. Petzold, L.](http://dx.doi.org/10.1016/j.jcp.2005.06.012) Accuracy limitations and the measurement of errors in the stochastic simulation of chemically reacting systems, 2006.
Although this paper's focus is on comparing stochastic simulation algorithms, essentially ... | null | CC BY-SA 2.5 | null | 2011-02-19T22:11:05.970 | 2011-02-19T22:11:05.970 | null | null | 8 | null |
7406 | 2 | null | 7211 | 0 | null | Andrew McCallum (UMass) has a few NLP related software projects available on his [webpage](http://www.cs.umass.edu/~mccallum/code.html). These are all in Java (I think) with source code available.
| null | CC BY-SA 2.5 | null | 2011-02-19T22:26:45.590 | 2011-02-19T22:26:45.590 | null | null | 1913 | null |
7407 | 1 | null | null | 6 | 300 | I recently stumbled upon the concept of [sample complexity](http://www.google.com/search?q=%22sample%20complexity%22), and was wondering if there are any texts, papers or tutorials that provide:
- An introduction to the concept (rigorous or informal)
- An analysis of the sample complexity of established and popular c... | Measuring and analyzing sample complexity | CC BY-SA 3.0 | null | 2011-02-19T22:41:23.000 | 2014-10-28T12:27:00.393 | 2012-05-02T14:19:06.373 | 2798 | 2798 | [
"machine-learning"
] |
7408 | 1 | 7409 | null | 4 | 890 | Here's a real basic question. I'm trying to teach myself a bit of stats with Verzani's Using R for Introductory Statistics.
In question 5.13 he asks: A sample of 100 people is drawn from a population of 600,000. If it is known that 40% of the population has a specific attribute, what is the probability that 35 or fewer... | Sampling from a fixed population | CC BY-SA 2.5 | null | 2011-02-19T23:46:53.130 | 2011-02-20T00:44:16.023 | null | null | 3317 | [
"self-study",
"sampling"
] |
7409 | 2 | null | 7408 | 9 | null | When sampling without replacement, the distribution is a hypergeometric one. The problem is usually presented as follows: in an urn with $n$ (600.000) marbles, $m$ (40% = 240.000) are red, $n-m$ (60% = 360.000) are black. What is the probability of picking $r$ (35) red marbles in a sample of $k$ (100) marbles? The erro... | null | CC BY-SA 2.5 | null | 2011-02-20T00:05:12.063 | 2011-02-20T00:44:16.023 | 2011-02-20T00:44:16.023 | 1909 | 1909 | null |
7410 | 2 | null | 7400 | 30 | null | The standard answer to this question is the [chi-squared test](http://www.itl.nist.gov/div898/handbook/eda/section3/eda35f.htm). The KS test is for unbinned data, not binned data. (If you have the unbinned data, then by all means use a KS-style test, but if you only have the histogram, the KS test is not appropriate.)
| null | CC BY-SA 2.5 | null | 2011-02-20T06:29:59.583 | 2011-02-20T06:29:59.583 | null | null | 21874 | null |
7411 | 2 | null | 3 | 3 | null | [Meta.Numerics](https://web.archive.org/web/20110123164637/http://www.meta-numerics.net/) is a .NET library with good support for statistical analysis.
Unlike R (an S clone) and Octave (a Matlab clone), it does not have a "front end". It is more like GSL, in that it is a library that you link to when you are writing yo... | null | CC BY-SA 4.0 | null | 2011-02-20T07:03:34.513 | 2022-11-27T23:08:57.587 | 2022-11-27T23:08:57.587 | 362671 | 21874 | null |
7412 | 1 | null | null | 4 | 1926 | I want to model how traffic will flow on real networks (not just the internet, also, say, Intel's internal LAN).
Is there a place I can get real network topologies data I can use?
| Where can I get real data of big network topology? | CC BY-SA 2.5 | null | 2011-02-20T08:03:25.657 | 2012-06-04T09:15:27.240 | null | null | 3328 | [
"networks",
"topologies"
] |
7413 | 2 | null | 7211 | 4 | null | Here are two further integrated projects:
- Python Natural Language Toolkit (easy installation, good documentation)
- Java MALLET (no experience with it, but looks promising; included in the link given by @Nick)
Both are open-source software.
| null | CC BY-SA 2.5 | null | 2011-02-20T09:20:16.843 | 2011-02-20T09:20:16.843 | null | null | 930 | null |
7414 | 2 | null | 6234 | 11 | null | This won't compete with @Shane's answer because circular displays are really well suited for displaying complex relationships with high-dimensional datasets.
For Venn diagrams, I've been using the [venneuler](http://cran.r-project.org/web/packages/venneuler/index.html) R package. It has a simple yet intuitive interface... | null | CC BY-SA 2.5 | null | 2011-02-20T09:40:05.920 | 2011-02-20T09:48:31.850 | 2011-02-20T09:48:31.850 | 930 | 930 | null |
7415 | 1 | null | null | 10 | 25072 | What are the statistical techniques to create a sample set, which is representative of the entire population (with a known confidence level)?
Also,
- How to validate, if the sample fits the overall dataset?
- Is it possible, without parsing the entire dataset (which could be billions of records)?
| How to make representative sample set from a large overall dataset? | CC BY-SA 2.5 | null | 2011-02-20T09:54:18.693 | 2011-02-20T19:28:51.147 | 2011-02-20T09:56:10.747 | 930 | 3292 | [
"sampling",
"sample-size",
"validation"
] |
7416 | 2 | null | 7048 | 8 | null | In addition to linking quantitative or qualitative data to spatial patterns, as illustrated by @whuber, I would like to mention the use of EDA, with brushing and the various of linking plots together, for longitudinal and high-dimensional data analysis.
Both are discussed in the excellent book, [Interactive and Dynami... | null | CC BY-SA 2.5 | null | 2011-02-20T10:46:02.080 | 2011-02-20T10:46:02.080 | null | null | 930 | null |
7417 | 2 | null | 7389 | 5 | null | I used paired t-test to compare my algorithm to GA, although I had about 200 test cases. You can use a non-parametric alternative such as the Wilcoxon Ranks Test. Regardless of what you use to test the statistical significance, bear in mind the "real-life" significance. If the performance improvement that your algorit... | null | CC BY-SA 3.0 | null | 2011-02-20T11:18:24.227 | 2014-02-05T20:13:19.270 | 2014-02-05T20:13:19.270 | 35895 | 1496 | null |
7418 | 2 | null | 7385 | 12 | null | For R two options spring to mind, both of which I am only vaguely familiar with at best.
The first is the `pscl` package, which can fit zero truncated inflated and hurdle models in a very nice, flexible manner. The `pscl` package suggests the use of the `sandwich` package which provides "Model-robust standard error est... | null | CC BY-SA 3.0 | null | 2011-02-20T11:51:29.197 | 2012-01-21T18:35:40.003 | 2012-01-21T18:35:40.003 | 1390 | 1390 | null |
7419 | 1 | 7674 | null | 10 | 1588 | I have been doing some casual internet research on biclusters. (I have read the Wiki article several times.) So far, it seems as if there are few definitions or standard terminology.
- I was wondering if there were any standard papers or books that anybody who is interested in algorithms for finding biclusters shoul... | Getting started with biclustering | CC BY-SA 2.5 | null | 2011-02-20T12:13:24.220 | 2011-12-21T08:32:30.810 | 2011-12-21T08:32:30.810 | 264 | 847 | [
"clustering",
"data-mining"
] |
7420 | 2 | null | 7415 | 2 | null | On your second question first, you might ask, "how was the data entered?" If you think that the data was entered in a relatively arbitrary fashion (i.e., independent of any observable or unobservable characteristics of your observations that might influence your ultimate analysis using the data), then you might conside... | null | CC BY-SA 2.5 | null | 2011-02-20T16:16:58.580 | 2011-02-20T16:24:28.540 | 2011-02-20T16:24:28.540 | 401 | 401 | null |
7422 | 1 | null | null | 3 | 1663 | I have network traffic data in the following for for each hour of a ten day period as follows in a R dataset.
```
Day Hour Volume Category
0 00 100 P2P
0 00 50 email
0 00 200 gaming
0 00 200 ... | Calculating hourly volatility and peak-to-average ratio in R | CC BY-SA 2.5 | null | 2011-02-20T16:48:57.387 | 2011-02-21T14:28:56.023 | 2011-02-21T14:28:56.023 | 919 | 2101 | [
"r",
"aggregation"
] |
7423 | 2 | null | 7422 | 2 | null | Check out the [plyr package](http://cran.r-project.org/web/packages/plyr/index.html), which has [great documentation](http://had.co.nz/plyr/). While you could solve your problem with `aggregate()` function, I'd argue that learning the plyr family of functions will be worth it in the end.
For your specific problem, this... | null | CC BY-SA 2.5 | null | 2011-02-20T18:24:48.317 | 2011-02-20T18:24:48.317 | null | null | 364 | null |
7424 | 2 | null | 7415 | 8 | null | If you don't wish to parse the entire data set then you probably can't use [stratified sampling](http://en.wikipedia.org/wiki/Stratified_sampling), so I'd suggest taking a large [simple random sample](http://en.wikipedia.org/wiki/Simple_random_sample). By taking a random sample, you ensure that the sample will, on aver... | null | CC BY-SA 2.5 | null | 2011-02-20T18:49:31.990 | 2011-02-20T19:28:51.147 | 2011-02-20T19:28:51.147 | 449 | 449 | null |
7425 | 2 | null | 7175 | 7 | null | I think the best quality measure for clustering is the cluster assumption, as given by Seeger in [Learning with labeled and unlabeled data](http://webcache.googleusercontent.com/search?q=cache:http://people.kyb.tuebingen.mpg.de/seeger/papers/review.pdf):
>
For example, assume X = Rd and the validity of the “cluster as... | null | CC BY-SA 3.0 | null | 2011-02-20T19:52:06.927 | 2013-07-02T04:33:56.040 | 2013-07-02T04:33:56.040 | 7290 | 2860 | null |
7426 | 1 | 7428 | null | 3 | 11200 | How can I conduct an Egger's test using SPSS17? For each study included in the meta-analysis I know effect size and sample size of patients and controls groups.
| Egger's test in SPSS | CC BY-SA 2.5 | null | 2011-02-20T21:27:02.557 | 2011-02-23T04:50:37.073 | 2011-02-20T23:42:57.017 | null | 3333 | [
"spss",
"meta-analysis",
"funnel-plot",
"publication-bias"
] |
7427 | 2 | null | 7426 | 2 | null | I don't use PASW anymore, but implementation of the Egger's test for asymmetry is quite simple. First please look at the Egger's [paper](http://goo.gl/6gnEj) where he propose "theory" behind the test.
Basically you have two variables: (i) normalized effect estimate (your estimate divided by its standard error), and (ii... | null | CC BY-SA 2.5 | null | 2011-02-20T21:53:59.553 | 2011-02-23T04:50:37.073 | 2011-02-23T04:50:37.073 | 609 | 609 | null |
7428 | 2 | null | 7426 | 5 | null | In order to conduct Egger's regression test you will also need the standard errors ($SE_i$) of your effect sizes ($ES_i$). Then generate the so called standard normal deviate (SND) which is defined as effect size divided by its standard error ($ES_i / SE_i$). Next, generate the precision which is $\frac{1}{SE_i}$. The ... | null | CC BY-SA 2.5 | null | 2011-02-20T22:12:41.893 | 2011-02-20T22:12:41.893 | 2017-04-13T12:44:29.013 | -1 | 307 | null |
7429 | 1 | 7431 | null | 4 | 5551 | What should I do if the expected value in a Chi-square goodness-of-fit test is zero?
I know there's Fisher's test but I have a very large table!
| Computing chi-square for large tables with some expected cell counts equal to zero | CC BY-SA 2.5 | null | 2011-02-21T00:53:30.507 | 2011-02-21T08:14:45.830 | 2011-02-21T08:08:14.360 | 449 | 3338 | [
"chi-squared-test",
"goodness-of-fit"
] |
7430 | 1 | 7434 | null | 7 | 8274 | A uniform prior for a scale parameter (like the variance) is uniform on the logarithmic scale.
What functional form does this prior have on the linear scale? And why so?
| Creating a uniform prior on the logarithmic scale | CC BY-SA 2.5 | null | 2011-02-21T02:44:28.760 | 2019-06-30T03:10:08.347 | 2011-02-21T05:59:30.047 | 183 | 1098 | [
"bayesian",
"prior"
] |
7431 | 2 | null | 7429 | 6 | null | If the expected value of a cell is zero in a goodness of fit test (I'm assuming you really mean goodness of fit, where the fit is to a theoretical distribution, not another observed distribution) then there are two possibilities:
- You also observed this value zero times. Just discard the zero expected value and try ... | null | CC BY-SA 2.5 | null | 2011-02-21T02:54:03.923 | 2011-02-21T02:54:03.923 | null | null | 1347 | null |
7432 | 1 | null | null | 5 | 10621 | In SPSS Version 19 there seems to be a new feature called Automatic Linear Modelling. It creates a 'Model' (which is new to me) and the function seems to combine a number of the functions that is typically required for prediction model development.
The functionality seems incomplete with only a subset of prediction se... | Is automatic linear modelling in SPSS a good or bad thing? | CC BY-SA 3.0 | null | 2011-02-21T03:21:45.580 | 2011-08-18T21:40:36.737 | 2011-08-18T18:13:53.687 | null | 3189 | [
"regression",
"modeling",
"spss"
] |
7433 | 2 | null | 7432 | 5 | null | I had a quick look at the [IBM SPSS advertising material](ftp://public.dhe.ibm.com/common/ssi/ecm/en/ytd03023usen/YTD03023USEN.PDF).
It sounds like it is part of a general move on the part of IBM/SPSS to get involved with predictive analytics.
Terms like automatic data preparation, boosting, bagging, and automated mode... | null | CC BY-SA 2.5 | null | 2011-02-21T03:36:42.370 | 2011-02-21T05:38:03.153 | 2011-02-21T05:38:03.153 | 183 | 183 | null |
7434 | 2 | null | 7430 | 15 | null | It's just a standard change of variables; the (monotone & 1-1) transformation is $y = \exp(x)$ with inverse $x=\log(y)$ and Jacobian $\frac{dx}{dy} = \frac{1}{y}$.
With a uniform prior $p_y(y) \propto 1$ on $\mathbb{R}$ we get $p_x(x) = p_y(x(y)) |\frac{dx}{dy}| \propto \frac{1}{y}$ on $(0, \infty)$.
Edit: Wikipedia h... | null | CC BY-SA 2.5 | null | 2011-02-21T05:27:07.727 | 2011-02-21T07:00:52.987 | 2011-02-21T07:00:52.987 | 26 | 26 | null |
7435 | 2 | null | 7402 | 1 | null | To supplement caracal's answer, if you are looking for a user-friendly GUI option for calculating Type II error rates or power for many common designs including the ones implied by your question, you may wish to check out the free software, [G Power 3](http://www.psycho.uni-duesseldorf.de/abteilungen/aap/gpower3/).
| null | CC BY-SA 2.5 | null | 2011-02-21T06:37:28.657 | 2011-02-21T06:37:28.657 | null | null | 183 | null |
7436 | 2 | null | 7429 | 3 | null | If you are using [Pearson's chi-square test as a test independence](http://en.wikipedia.org/wiki/Pearson%27s_chi-square_test#Test_of_independence) of two variables in a two-way [contingency table](http://en.wikipedia.org/wiki/Contingency_table), you'll get a zero expected value only if you have a whole row of zeroes or... | null | CC BY-SA 2.5 | null | 2011-02-21T08:14:45.830 | 2011-02-21T08:14:45.830 | null | null | 449 | null |
7438 | 1 | null | null | 1 | 10776 | As a basic question in Regression Analysis, I wanted to ask how can I calculate Margin of Error when I fit a straight line to a set of data.
Assume that I have variation of parameter $A$ as a function of parameter $B$, then $A=mB \pm e$, where $m$ is the tangent of the fitted straight line and $e$ is what i'm looking f... | How to calculate margin of error in linear regression? | CC BY-SA 2.5 | null | 2011-02-21T09:57:19.063 | 2011-02-21T19:18:51.447 | 2011-02-21T10:07:55.150 | 2116 | null | [
"regression"
] |
7439 | 1 | 7444 | null | 33 | 61965 | You can have data in wide format or in long format.
This is quite an important thing, as the useable methods are different, depending on the format.
I know you have to work with `melt()` and `cast()` from the reshape package, but there seems some things that I don't get.
Can someone give me a short overview how you do ... | How to change data between wide and long formats in R? | CC BY-SA 2.5 | null | 2011-02-21T10:27:05.680 | 2016-05-10T18:01:17.903 | 2011-02-21T16:30:39.317 | 8 | 3140 | [
"data-transformation",
"r"
] |
7440 | 1 | 7449 | null | 143 | 176928 | I need to determine the KL-divergence between two Gaussians. I am comparing my results to [these](http://allisons.org/ll/MML/KL/Normal/), but I can't reproduce their result. My result is obviously wrong, because the KL is not 0 for KL(p, p).
I wonder where I am doing a mistake and ask if anyone can spot it.
Let $p(x) =... | KL divergence between two univariate Gaussians | CC BY-SA 4.0 | null | 2011-02-21T10:30:18.527 | 2022-12-27T09:52:24.333 | 2022-12-27T09:31:54.853 | 362671 | 2860 | [
"normal-distribution",
"kullback-leibler"
] |
7441 | 2 | null | 7438 | 2 | null | It seems that you want the residuals of linear regression without the intercept term where dependent variable is $A$ and the independent variable is $B$. This can be done with various statistical packages. Here is the implementation in R.
```
aa <-"(39.7678, 2320.3}, {30.8438, 1614.21}, {125.846, 3078.81}, {55.2345, 1... | null | CC BY-SA 2.5 | null | 2011-02-21T10:30:24.187 | 2011-02-21T19:18:51.447 | 2011-02-21T19:18:51.447 | 2116 | 2116 | null |
7443 | 2 | null | 7440 | 56 | null | I did not have a look at your calculation but here is mine with a lot of details.
Suppose $p$ is the density of a normal random variable with mean $\mu_1$ and variance $\sigma^2_1$, and that $q$ is the density of a normal random variable with mean $\mu_2$ and variance $\sigma^2_2$.
The Kullback-Leibler distance from $q... | null | CC BY-SA 4.0 | null | 2011-02-21T10:58:18.427 | 2022-12-27T09:52:24.333 | 2022-12-27T09:52:24.333 | 362671 | 3019 | null |
7444 | 2 | null | 7439 | 29 | null | There are several resources on Hadley Wickham's [website](http://had.co.nz/reshape/) for the package (now called `reshape2`), including a link to a [paper](http://www.jstatsoft.org/v21/i12) on the package in the Journal of Statistical Software.
Here is a brief example from the paper:
```
> require(reshape2)
Loading req... | null | CC BY-SA 2.5 | null | 2011-02-21T11:09:33.423 | 2011-02-21T11:09:33.423 | null | null | 1390 | null |
7446 | 2 | null | 7439 | 8 | null |
- Quick-R has simple example of using reshape package
- See also ?reshape (LINK) for the Base R way of moving between wide and long format.
| null | CC BY-SA 2.5 | null | 2011-02-21T11:14:36.693 | 2011-02-21T11:14:36.693 | null | null | 183 | null |
7447 | 1 | null | null | 15 | 4577 | Both [Root Mean Square](http://en.wikipedia.org/wiki/Root_mean_square) and [Average absolute deviation](http://en.wikipedia.org/wiki/Absolute_deviation#Average_absolute_deviation) seem like the measures of the magnitude of variability (especially when the variates are both +ve and -ve). What are the rules of thumb to c... | Root mean square vs average absolute deviation? | CC BY-SA 2.5 | null | 2011-02-21T11:40:25.130 | 2011-02-21T11:52:42.560 | 2011-02-21T11:50:01.563 | null | 3292 | [
"regression",
"standard-deviation"
] |
7448 | 2 | null | 7447 | 16 | null | In theory, this should be determined by how important different sized errors are to you, or in other words, your loss function.
In the real world, people put ease of use first. So RMS deviations (or the related variances) are easier to combine, and easier to calculate in a single pass, while average absolute deviati... | null | CC BY-SA 2.5 | null | 2011-02-21T11:52:42.560 | 2011-02-21T11:52:42.560 | null | null | 2958 | null |
7449 | 2 | null | 7440 | 103 | null | OK, my bad. The error is in the last equation:
\begin{align}
KL(p, q) &= - \int p(x) \log q(x) dx + \int p(x) \log p(x) dx\\\\
&=\frac{1}{2} \log (2 \pi \sigma_2^2) + \frac{\sigma_1^2 + (\mu_1 - \mu_2)^2}{2 \sigma_2^2} - \frac{1}{2} (1 + \log 2 \pi \sigma_1^2)\\\\
&= \log \frac{\sigma_2}{\sigma_1} + \frac{\sigma_1^2 + ... | null | CC BY-SA 3.0 | null | 2011-02-21T11:55:19.103 | 2022-12-27T08:40:09.397 | 2022-12-27T08:40:09.397 | 2116 | 2116 | null |
7450 | 1 | null | null | 12 | 5193 | I have a problem with the estimation parameter for Zipf. My situation is the following:
I have a sample set (measured from an experiment that generates calls that should follow a Zipf distribution). I have to demonstrate that this generator really generates calls with zipf distribution.
I already read this Q&A [How t... | How to estimate parameters for Zipf truncated distribution from a data sample? | CC BY-SA 2.5 | null | 2011-02-21T13:51:50.393 | 2011-04-08T01:51:15.640 | 2017-04-13T12:44:41.980 | -1 | 3342 | [
"distributions",
"estimation",
"pareto-distribution",
"zipf"
] |
7452 | 2 | null | 7450 | 5 | null | The paper
Clauset, A et al, [Power-law Distributions in Empirical Data](http://arxiv.org/abs/0706.1062). 2009
contains a very good description of how to go about fitting power law models. The associated [web-page](http://tuvalu.santafe.edu/~aaronc/powerlaws/) has code samples. Unfortunately, it doesn't give code for tr... | null | CC BY-SA 2.5 | null | 2011-02-21T14:36:44.550 | 2011-02-21T14:36:44.550 | null | null | 8 | null |
7454 | 2 | null | 7439 | 7 | null | You don't have to use `melt` and `cast`.
Reshaping data can be done lots of ways. In your particular example on your cite using `recast` with `aggregate` was redundant because `aggregate` does the task fine all on it's own.
```
aggregate(cbind(LPMVTUZ, LPMVTVC, LPMVTXC) ~ year, dtm, sum)
# or even briefer by first r... | null | CC BY-SA 3.0 | null | 2011-02-21T15:25:54.473 | 2014-05-25T07:14:03.977 | 2014-05-25T07:14:03.977 | 601 | 601 | null |
7455 | 1 | 7473 | null | 16 | 4726 | Can someone refer me to a good reference that explains the connection between Bayesian statistics and generative modeling techniques? Why do we usually use generative models with Bayesian techniques?
Why it is especially appealing to use Bayesian statistics in the absence of complete data, if at all?
Note that I come f... | The connection between Bayesian statistics and generative modeling | CC BY-SA 2.5 | null | 2011-02-21T16:34:03.293 | 2012-10-16T13:51:01.003 | 2011-02-22T07:53:42.247 | 2116 | 3347 | [
"bayesian",
"generative-models"
] |
7456 | 2 | null | 7438 | 3 | null | You are asking to estimate the typical size of the error. This is usually done by estimating the variance of the random variable $e$ and taking its square root. It is often called the "root mean square error".
These data look like they are formatted for Mathematica. A Mathematica 8 solution is
```
{a, b} = {{39.7678... | null | CC BY-SA 2.5 | null | 2011-02-21T16:44:01.187 | 2011-02-21T16:44:01.187 | null | null | 919 | null |
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