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10468 | 2 | null | 10450 | 0 | null | Here's an older answer to a similar question on SO. It has some code that you could try/modify:
[Similar Question](https://stackoverflow.com/questions/1040324/how-to-generate-pseudo-random-positive-definite-matrix-with-constraints-on-the-of)
Some other links:
[Forecasting Covariance Matrices](http://www.oxford-man.ox... | null | CC BY-SA 3.0 | null | 2011-05-07T16:01:26.687 | 2011-05-11T15:03:29.787 | 2017-05-23T12:39:26.143 | -1 | 2775 | null |
10469 | 2 | null | 10459 | 4 | null | There are several movie versions of [Flatland](http://en.wikipedia.org/wiki/Flatland). And there's The Great $\pi$/e Debate.
| null | CC BY-SA 3.0 | null | 2011-05-07T16:13:17.890 | 2011-05-07T19:40:38.563 | 2011-05-07T19:40:38.563 | 264 | 3874 | null |
10470 | 2 | null | 10459 | 10 | null | [N Is a Number: A Portrait of Paul Erdős](http://zalafilms.com/films/nisanumber.html)
| null | CC BY-SA 3.0 | null | 2011-05-07T16:26:44.237 | 2011-05-07T16:26:44.237 | null | null | 22 | null |
10471 | 2 | null | 10459 | 4 | null | Early in [The Social Network](http://en.wikipedia.org/wiki/The_Social_Network#Plot) begins with a one night hackathon where Mark Zuckerberg uses the [Elo rating system algorithm](http://en.wikipedia.org/wiki/Elo_rating_system) to
>
... create a website that rates the attractiveness of female students
when compared t... | null | CC BY-SA 3.0 | null | 2011-05-07T17:20:21.900 | 2011-05-07T17:20:21.900 | null | null | 4508 | null |
10472 | 2 | null | 10459 | 10 | null | [Proof](http://www.imdb.com/title/tt0377107/) was pretty good.
| null | CC BY-SA 3.0 | null | 2011-05-07T17:43:25.480 | 2011-05-07T17:43:25.480 | null | null | 3748 | null |
10473 | 2 | null | 10366 | 1 | null | If your penultimate goal is to embed your plot in a Latex document, you might consider using the [gnuplottex](ftp://ftp.dante.de/tex-archive/help/Catalogue/entries/gnuplottex.html) package (as an alternative to [pgfplots](http://ctan.org/pkg/pgfplots) which is an awesome package). The idea is rather simple: you write y... | null | CC BY-SA 3.0 | null | 2011-05-07T18:40:09.827 | 2011-05-07T18:40:09.827 | null | null | 930 | null |
10474 | 2 | null | 10459 | 11 | null | Not a movie, but a TV series:
[Numb3rs](http://en.wikipedia.org/wiki/Numb3rs)
| null | CC BY-SA 3.0 | null | 2011-05-07T18:40:18.220 | 2011-05-07T18:40:18.220 | null | null | 264 | null |
10475 | 2 | null | 7045 | 4 | null | I would suggest trying the [glmnet package](http://cran.r-project.org/web/packages/glmnet/index.html) for feature selection. glmnet uses the [elastic net](http://citeseer.ist.psu.edu/viewdoc/download;jsessionid=6DD6392682DB8F43219A2C81171B64CF?doi=10.1.1.124.4696&rep=rep1&type=pdf) for regularization and feature selec... | null | CC BY-SA 3.0 | null | 2011-05-07T18:54:02.790 | 2011-05-07T18:54:02.790 | null | null | 2817 | null |
10476 | 2 | null | 10459 | 8 | null | [21](http://www.imdb.com/title/tt0478087/) - based on the book Bringing Down the House (MIT Blackjack team)
Near the beginning they discuss the Monty Hall Problem. However after that there isn't much actual math/probability.
| null | CC BY-SA 3.0 | null | 2011-05-07T18:56:38.453 | 2011-05-07T23:56:16.110 | 2011-05-07T23:56:16.110 | 4360 | 2310 | null |
10477 | 2 | null | 10459 | 5 | null | I have not seen this yet, but it seems somewhat geeky:
[Fermat's Room](http://www.imdb.com/title/tt1016301/)
| null | CC BY-SA 3.0 | null | 2011-05-07T19:25:34.977 | 2011-05-07T19:25:34.977 | null | null | 795 | null |
10478 | 1 | 277016 | null | 15 | 5009 | Are there any analytical results or experimental papers regarding the optimal choice of the coefficient of the $\ell_1$ penalty term. By optimal, I mean a parameter that maximizes the probability of selecting the best model, or that minimizes the expected loss. I am asking because often it is impractical to choose the ... | Optimal penalty selection for lasso | CC BY-SA 3.0 | null | 2011-05-07T22:37:35.410 | 2022-08-27T18:48:57.300 | 2011-05-07T23:57:03.037 | null | 30 | [
"model-selection",
"lasso",
"regularization"
] |
10479 | 2 | null | 9715 | 1 | null | You could also try running a multinomial logit using the glmnet package. I'm not sure how to force it to keep all variables, but I'm sure it's possible.
| null | CC BY-SA 3.0 | null | 2011-05-07T22:51:34.940 | 2011-05-07T22:51:34.940 | null | null | 2817 | null |
10480 | 1 | 10485 | null | 5 | 3796 | This is a homework problem out of the book. It says
>
If $U$ is a uniform random variable on [0,1], what is the distribution of the random variable $X = [nU]$, where [$t$] denotes the greatest integer less than or equal to $t$?
There is a second part that says
>
Do this for $n = 10$. True or false, and explain: “R... | Uniform random variable distribution | CC BY-SA 3.0 | null | 2011-05-07T23:24:21.390 | 2011-05-08T04:51:12.043 | null | null | 4401 | [
"distributions",
"self-study",
"uniform-distribution"
] |
10481 | 2 | null | 10480 | 3 | null | $t$ is just a placeholder name for a variable, the actual focus in that explanation is on the square brackets which refer to the [floor](http://en.wikipedia.org/wiki/Floor_and_ceiling_functions) function.
I would start by plotting the function that maps from $U$ to $X$, that is $X(u)=[nu]$ in the range of all the value... | null | CC BY-SA 3.0 | null | 2011-05-07T23:38:16.203 | 2011-05-08T04:51:12.043 | 2011-05-08T04:51:12.043 | 2116 | 4360 | null |
10482 | 1 | null | null | 3 | 510 | I was impressed by the Reputation histogram on the SE sites allowing one to zoom in to any time interval. How was it created?
| How to create histogram with "zoom-in" feature | CC BY-SA 3.0 | null | 2011-05-07T23:00:27.467 | 2011-05-07T23:53:52.087 | 2011-05-07T23:53:52.087 | null | null | [
"data-visualization"
] |
10483 | 2 | null | 10482 | 5 | null | This is a barplot rather than histogram... Anyway, judging from the page source, it is made with [Highcharts JS](http://www.highcharts.com/).
| null | CC BY-SA 3.0 | null | 2011-05-07T23:51:42.400 | 2011-05-07T23:51:42.400 | null | null | null | null |
10484 | 1 | 10489 | null | 10 | 675 | I have some data in R, stored in a list. Think
```
d <- c(1,2,3,4)
```
although this is not my data. If I then enter the command
```
plot(density(d, kernel="gaussian", width=1))
```
then I get the kernel probability density estimate, where the kernel is standard normal. If I replace 1 with other numbers, of course ... | Animating the effect of changing kernel width in R | CC BY-SA 3.0 | null | 2011-05-08T00:25:47.643 | 2015-04-23T05:58:23.283 | 2015-04-23T05:58:23.283 | 9964 | 98 | [
"r",
"kernel-smoothing"
] |
10485 | 2 | null | 10480 | 5 | null | $[t]$ is the floor function, and $t$ just represents a generic argument. So for example $[0.5]=0$, $[0.9]=0$, $[1.01]=1$, $[1]=1$, $[23.567]=23$, and so on. You simply ignore whats written after the decimal point (note: this is not the same thing as rounding, for $[0.9]=0$ whereas rounding would give $1$.)
With non-s... | null | CC BY-SA 3.0 | null | 2011-05-08T00:45:37.190 | 2011-05-08T03:32:23.783 | 2011-05-08T03:32:23.783 | 2970 | 2392 | null |
10486 | 1 | null | null | 4 | 1803 | Suppose I want to predict Amazon or Netflix demand, using demand data over the past year. For example, I might want to forecast the number of sales in the Electronics category on Amazon, or the number of times someone wants to rent Titanic on Netflix. My dataset consists of daily demand per item over the past couple of... | Forecasting Amazon or Netflix demand | CC BY-SA 3.0 | null | 2011-05-08T00:51:51.530 | 2011-05-09T15:48:15.743 | 2011-05-08T02:27:15.560 | 2116 | 1106 | [
"time-series",
"forecasting"
] |
10487 | 2 | null | 10486 | 3 | null | When you have a number of Endogenous series possibly cross-related and a number of Exogenous series, this is referred to as a VECTOR ARIMA MODEL , a super-set of a VAR model and an ARIMA MODEL. We have resolved Daily forecasts for a Family TYpe and Daily forecasts for "children" or "subset categories" by incorporating... | null | CC BY-SA 3.0 | null | 2011-05-08T01:17:36.197 | 2011-05-08T02:40:32.763 | 2011-05-08T02:40:32.763 | 3382 | 3382 | null |
10488 | 2 | null | 10484 | 7 | null | One way to go is to use the excellent [animation](http://animation.yihui.name/animation%3astart) package by Yihui Xie. I uploaded a very simple example to my public dropbox account: [densityplot](http://dl.dropbox.com/u/6973449/RtmpeKvc2B/index.html) (I will remove this example in 3 days). Is this what you are looking ... | null | CC BY-SA 3.0 | null | 2011-05-08T02:16:55.657 | 2011-05-08T10:44:42.037 | 2011-05-08T10:44:42.037 | 307 | 307 | null |
10489 | 2 | null | 10484 | 11 | null | It depends a little bit on what your end goal is.
Quick and dirty hack for real-time demonstrations
Using `Sys.sleep(seconds)` in a loop where `seconds` indicates the number of seconds between frames is a viable option. You'll need to set the `xlim` and `ylim` parameters in your call to `plot` to make things behave as ... | null | CC BY-SA 3.0 | null | 2011-05-08T02:17:18.763 | 2011-05-08T02:17:18.763 | null | null | 2970 | null |
10490 | 2 | null | 6702 | 2 | null | To answer my own question, I've moved over to using the 'glmnet' package to fit my multinomial logits, which has the added advantage of using the lasso or elastic net to regularize my independent variables. glmnet seems to be a much more 'finished' packaged than mlogit, complete with a 'predict' function.
| null | CC BY-SA 3.0 | null | 2011-05-08T02:23:47.900 | 2011-05-08T02:23:47.900 | null | null | 2817 | null |
10491 | 2 | null | 73 | 4 | null | If you are doing any kind of predictive modeling, [caret](http://cran.r-project.org/web/packages/caret/index.html) is a godsend. Especially combined with the [multicore](http://cran.r-project.org/web/packages/multicore/index.html) package, some pretty amazing things are possible.
| null | CC BY-SA 3.0 | null | 2011-05-08T02:26:21.970 | 2011-05-08T02:26:21.970 | null | null | 2817 | null |
10492 | 2 | null | 3392 | 6 | null | Excel is no good for statistics, but it can be wonderful for exploratory data analysis. [Take a look at this video](http://www.r-bloggers.com/getting-into-shape-for-the-sport-of-data-science-screencast-of-talk-by-jeremy-howard-at-melbourne-r-users/) for some particularly interesting techniques. Excel's ability to con... | null | CC BY-SA 3.0 | null | 2011-05-08T02:32:10.377 | 2011-05-08T02:32:10.377 | null | null | 2817 | null |
10493 | 2 | null | 10486 | 4 | null | If you do a good enough job modeling the important predictor variables, you probably will not need to worry as much about the time series aspects (You should probably still test for serial correlation and adjust for it if needed).
Most of the times series style association you will see can easily be modeled by things l... | null | CC BY-SA 3.0 | null | 2011-05-08T02:49:16.147 | 2011-05-09T15:48:15.743 | 2011-05-09T15:48:15.743 | 4505 | 4505 | null |
10494 | 2 | null | 3392 | 7 | null | Another good reference source for why you might not want to use excel is:
[Spreadsheet addiction](http://www.burns-stat.com/pages/Tutor/spreadsheet_addiction.html)
If you find yourself in a situation where you really need to use excel (some accademic departments insist), then I would suggest using the [Rexcel plugin](h... | null | CC BY-SA 3.0 | null | 2011-05-08T03:01:16.803 | 2011-05-08T03:01:16.803 | null | null | 4505 | null |
10495 | 2 | null | 10484 | 4 | null | Here is another approach:
```
library(TeachingDemos)
d <- c(1,2,3,4)
tmpfun <- function(width=1, kernel='gaussian'){
plot(density(d, width=width, kernel=kernel))
}
tmplst <- list( width=list('slider', init=1, from=.5, to=5, resolution=.1),
kernel=list('radiobuttons', init='gaussian', values=c('gaussian',
... | null | CC BY-SA 3.0 | null | 2011-05-08T03:22:27.187 | 2011-05-08T03:22:27.187 | null | null | 4505 | null |
10496 | 2 | null | 10484 | 5 | null | Just for the sake of completeness, if you need this for a class demonstration, I would also mention the `manipulate` package which comes with [RStudio](http://www.rstudio.org/). Note that this package is dependent on RStudio interface, so it won't work outside of it.
`manipulate` is quite cool because it allows to quic... | null | CC BY-SA 3.0 | null | 2011-05-08T05:01:33.230 | 2011-05-08T05:01:33.230 | null | null | 582 | null |
10497 | 1 | 10548 | null | 7 | 1974 | I became interested in doing this in C# for my own amusement after reading the following papers:
[http://www.cs.washington.edu/homes/brun/pubs/pubs/Kiddon11.pdf](http://www.cs.washington.edu/homes/brun/pubs/pubs/Kiddon11.pdf)
I also took a look at [http://www.cs.rpi.edu/academics/courses/fall03/ai/misc/naive-example.pd... | Naive Bayes classification for "That's what she said" problem | CC BY-SA 3.0 | null | 2011-05-08T05:08:07.753 | 2011-05-09T19:59:17.390 | 2011-05-08T20:02:33.823 | 4513 | 4513 | [
"machine-learning",
"naive-bayes"
] |
10498 | 2 | null | 8807 | 1 | null | I can recomend you 2 interesting papers to read that are online
1.[Streamed Learning: One-Pass SVMs, by Piyush Rai, Hal Daum´e III, Suresh Venkatasubramanian](https://www.ijcai.org/Proceedings/09/Papers/204.pdf)
2.[Streaming k-means approximation, by Nir Ailon](http://www1.cs.columbia.edu/%7Erjaiswal/ajmNIPS09.pdf)
Hop... | null | CC BY-SA 4.0 | null | 2011-05-08T05:51:21.903 | 2022-07-12T14:24:45.640 | 2022-07-12T14:24:45.640 | -1 | 1808 | null |
10499 | 2 | null | 10478 | 5 | null | I take it that you are mostly interested in regression, as in the cited paper, and not other applications of the $\ell_1$-penalty (graphical lasso, say).
I then believe that some answers can be found in the paper [On the “degrees of freedom” of the lasso](https://projecteuclid.org/journals/annals-of-statistics/volume-3... | null | CC BY-SA 4.0 | null | 2011-05-08T07:10:23.307 | 2022-08-27T18:48:57.300 | 2022-08-27T18:48:57.300 | 79696 | 4376 | null |
10500 | 2 | null | 10459 | 9 | null | [The Cube](http://en.wikipedia.org/wiki/Cube_%28film%29)
| null | CC BY-SA 3.0 | null | 2011-05-08T07:16:23.570 | 2011-05-08T07:16:23.570 | null | null | 4376 | null |
10501 | 1 | 226972 | null | 21 | 24332 | It is easy to find a package calculating area under ROC, but is there a package that calculates the area under precision-recall curve?
| Calculating AUPR in R | CC BY-SA 3.0 | null | 2011-05-08T07:32:35.350 | 2019-07-17T15:54:06.683 | null | null | null | [
"r",
"precision-recall"
] |
10502 | 2 | null | 10501 | 2 | null | A little googling returns one bioc package, [qpgraph](http://www.bioconductor.org/packages/2.4/bioc/html/qpgraph.html) (`qpPrecisionRecall`), and a cran one, [minet](http://cran.r-project.org/web/packages/minet/) (`auc.pr`). I have no experience with them, though. Both have been devised to deal with biological networks... | null | CC BY-SA 3.0 | null | 2011-05-08T08:17:15.270 | 2011-05-08T08:17:15.270 | null | null | 930 | null |
10503 | 1 | null | null | 4 | 198 | I have a set of data (positive real numbers < 1) in five categories. My aim is to show that the data in the last category is bigger than the other categories for a range of examples (the data set), but the last category isn't necessarily more important than the others.
I thought the best thing is to average each catego... | Set of data and averaging/standard deviation | CC BY-SA 3.0 | null | 2011-05-08T08:44:12.670 | 2011-05-08T10:03:27.937 | 2011-05-08T10:03:27.937 | 4515 | 4515 | [
"standard-deviation",
"simulation",
"mean"
] |
10504 | 2 | null | 73 | 2 | null | lattice, car, MASS, foreign, party.
| null | CC BY-SA 3.0 | null | 2011-05-08T11:53:51.660 | 2011-05-08T11:53:51.660 | null | null | 686 | null |
10505 | 2 | null | 10497 | 1 | null | An interesting source of suggestions for this problem might be the [That's What She Said Quora thread](http://www.quora.com/How-would-you-programmatically-parse-a-sentence-and-decide-whether-to-answer-thats-what-she-said). Specifically, the first comment identifies that it might make sense to use Twitter streams as a s... | null | CC BY-SA 3.0 | null | 2011-05-08T12:13:10.863 | 2011-05-09T13:02:03.733 | 2011-05-09T13:02:03.733 | 1065 | 1065 | null |
10506 | 2 | null | 10382 | 2 | null | You need to check how others have built indexes with similar questions. My guess is that Inglehart and Norris, in [Rising Tide](http://www.hks.harvard.edu/fs/pnorris/Books/Rising%20tide.htm), have built their Gender Equality/Empowerment index in a way that you can emulate (the construction of the index escapes me but I... | null | CC BY-SA 3.0 | null | 2011-05-08T12:17:28.707 | 2011-05-08T12:17:28.707 | null | null | 3582 | null |
10507 | 2 | null | 10420 | 0 | null | The question is too vague as such, but any answer will depend on your object of study ([example](http://www.iq.harvard.edu/blog/sss/archives/2006/02/bayesian_vs_fre.shtml)). You will find tons on the topic over at [Andrew Gelman's blog](http://www.stat.columbia.edu/~cook/movabletype/archives/2011/04/bayesian_statis_1.h... | null | CC BY-SA 3.0 | null | 2011-05-08T12:31:33.807 | 2011-05-08T12:31:33.807 | null | null | 3582 | null |
10508 | 2 | null | 10497 | 1 | null | Here is a Web site that uses a classifier to determine the gender of an author of text:
```
http://bookblog.net/gender/genie.php
```
There are a number of articles on the subject at the Web site and the composer of the
site has written a number of articles on the subject as well. There are a number of
good meth... | null | CC BY-SA 3.0 | null | 2011-05-08T12:58:42.243 | 2011-05-08T12:58:42.243 | null | null | 3805 | null |
10510 | 1 | null | null | 67 | 5466 | In the last few years I've read a number of papers arguing against the use of null hypothesis significance testing in science, but didn't think to keep a persistent list. A colleague recently asked me for such a list, so I thought I'd ask everyone here to help build it. To start things off, here's what I have so far:
... | References containing arguments against null hypothesis significance testing? | CC BY-SA 4.0 | null | 2011-05-08T16:09:04.040 | 2022-08-27T12:03:06.130 | 2022-03-26T10:13:03.113 | 79696 | 364 | [
"hypothesis-testing",
"statistical-significance",
"references",
"p-value"
] |
10511 | 2 | null | 10510 | 44 | null | Chris Fraley has taught [a whole course on the history of the debate](http://www.uic.edu/classes/psych/psych548/fraley/) (the link seems to be broken, even though it's still on his official site; here is [a copy in Internet Archive](https://web.archive.org/web/20150430200302/http://www.uic.edu/classes/psych/psych548/fr... | null | CC BY-SA 3.0 | null | 2011-05-08T16:52:17.817 | 2016-12-06T13:56:36.520 | 2016-12-06T13:56:36.520 | 28666 | 3748 | null |
10513 | 2 | null | 3719 | 1 | null | Pearson correlations can be converted into 'z' scores. Those z scores may be averaged and their median converted back to the composit correlation
| null | CC BY-SA 3.0 | null | 2011-05-08T17:46:41.447 | 2011-05-08T17:46:41.447 | null | null | 4518 | null |
10514 | 2 | null | 10363 | -4 | null | r square of 97.2
Estimation/Diagnostic Checking for Variable Y Y
X1 AAS
X2 BB
X3 BBS
X4 CC
Number of Res... | null | CC BY-SA 3.0 | null | 2011-05-08T17:51:27.797 | 2011-05-08T17:51:27.797 | null | null | 3382 | null |
10515 | 2 | null | 10420 | 1 | null | In my experience, they are both useful in different situations.
Where you can confidently say that the data come from a specified probability model, then parametric statistics will usually give you more information. However, they can also lead to significantly biased conclusions if the wrong model is used.
Non-paramet... | null | CC BY-SA 3.0 | null | 2011-05-08T17:52:31.057 | 2011-05-08T17:52:31.057 | null | null | 656 | null |
10517 | 1 | null | null | 6 | 6073 | Given a sample data set of floating point numbers, how do we determine its probability distribution and prove it?
Also generate random numbers of the same distributions thereafter.
| Identify probability distributions | CC BY-SA 3.0 | null | 2011-05-08T18:56:08.370 | 2016-03-23T19:33:41.060 | null | null | 4520 | [
"distributions",
"probability",
"modeling",
"dataset",
"simulation"
] |
10518 | 2 | null | 10510 | 12 | null | These are excellent references. I have a perhaps useful handout at [http://hbiostat.org/bayes](http://hbiostat.org/bayes)
| null | CC BY-SA 4.0 | null | 2011-05-08T19:03:21.840 | 2022-08-27T12:03:06.130 | 2022-08-27T12:03:06.130 | 4253 | 4253 | null |
10519 | 1 | 10524 | null | 4 | 4259 | If I have many time series that I'd like to compare to see if there are relationships between the variables, (I have several dependent variables and many more independent variables) how might I go about doing this (I'm working in R, just fyi)? I haven't really found too many examples seeking to compare and explore the ... | Comparing multiple time series in R | CC BY-SA 3.0 | null | 2011-05-08T19:31:29.433 | 2011-05-08T22:37:39.683 | 2011-05-08T20:43:07.527 | null | 4521 | [
"r",
"time-series",
"multiple-comparisons"
] |
10520 | 2 | null | 10363 | 24 | null | $R^2$ alone is not a good measure of goodness of fit, but let's not get into that here except to observe that parsimony is valued in modeling.
To that end, note that standard techniques of [exploratory data analysis](https://en.wikipedia.org/wiki/Exploratory_data_analysis) (EDA) and regression (but not stepwise or othe... | null | CC BY-SA 3.0 | null | 2011-05-08T19:40:32.340 | 2013-10-05T15:00:21.693 | 2020-06-11T14:32:37.003 | -1 | 919 | null |
10522 | 2 | null | 10382 | 10 | null | People often use the phrase "Likert scale" erroneously, not realizing that it originally described the coherent method Rensis Likert developed to do just what you're describing. Key steps are
- Seeing how well each item correlates with "the whole"--the average of all other items
- Checking variability, since an ite... | null | CC BY-SA 4.0 | null | 2011-05-08T20:36:37.933 | 2018-05-08T20:17:37.590 | 2018-05-08T20:17:37.590 | 2669 | 2669 | null |
10523 | 1 | 10525 | null | 2 | 597 | I've been trying to replicate the results in this online calculator:
[http://www.raosoft.com/samplesize.html](http://www.raosoft.com/samplesize.html)
However, it seems that I am missing something. Exactly how do I solve the margin of error when all the other variables (sample size, confidence level, distribution and po... | Margin-of-error calculation in survey | CC BY-SA 3.0 | null | 2011-05-08T20:47:43.803 | 2011-05-08T21:27:25.250 | 2011-05-08T20:56:19.740 | 3401 | 3401 | [
"confidence-interval",
"standard-error"
] |
10524 | 2 | null | 10519 | 3 | null | here goes ... These are the steps that are required to form your analysis. Simply reproduce them in R or whatever tools you have available. The reason the following exercise is daunting is because the statistical problem you are asking is "daunting" and one needs to "up-armor" their solutions skills/procedures.
- pre-... | null | CC BY-SA 3.0 | null | 2011-05-08T20:53:30.243 | 2011-05-08T20:53:30.243 | null | null | 3382 | null |
10525 | 2 | null | 10523 | 5 | null | It is possible to reproduce the page's Javascript formula, for example in R (with some minor adjustments, notably treating the confidence figure as two-tailed, but leaving it with the slightly confusing calculations using percentages).
```
MarginOfError <- function(sample, confidence, response, population) ... | null | CC BY-SA 3.0 | null | 2011-05-08T21:27:25.250 | 2011-05-08T21:27:25.250 | null | null | 2958 | null |
10526 | 1 | 10600 | null | 7 | 1750 | Is there a way to utilize Canonical Correlation Analysis when your data are time series and repeated measures (i.e. your experimental units are not independent)? How might one approach the analysis of two sets of variables when the question is what relationships, if any, are there between one set of variables and the ... | Canonical correlation analysis and time series analysis | CC BY-SA 3.0 | null | 2011-05-08T21:47:17.597 | 2011-05-10T15:57:42.317 | 2011-05-09T08:34:03.113 | null | 4521 | [
"time-series",
"correlation",
"multivariate-analysis"
] |
10527 | 2 | null | 10363 | 3 | null | Broadly speaking, there's no free lunch in machine learning:
>
In particular, if algorithm A outperforms algorithm B on some cost functions, then loosely speaking there must exist exactly as many other functions where B outperforms A
/edit: also, a radial SVM with C = 4 and sigma = 0.206 easily yields an R2 of .99. ... | null | CC BY-SA 3.0 | null | 2011-05-08T21:53:41.973 | 2011-05-09T01:47:04.977 | 2011-05-09T01:47:04.977 | 2817 | 2817 | null |
10528 | 2 | null | 173 | 2 | null | In response to your direct question "How can I test if there's a real change in the process? And if I can identify a decline, how could I use that trend and whatever seasonality there might be to estimate the number of cases we might see in the upcoming months?" Develop a Transfer Function Model ( ARMAX ) that readily ... | null | CC BY-SA 3.0 | null | 2011-05-08T22:19:18.250 | 2011-09-22T12:29:10.747 | 2011-09-22T12:29:10.747 | 3382 | 3382 | null |
10529 | 1 | null | null | 5 | 505 | I am reviewing a study in which standard deviations (SDs) of an X variable, calculated for each individual in the study (measures on each individual were replicated 4 times), are used as predictors of a Y variable. They do not observe a significant correlation between Y and the SDs of X and they conclude by saying that... | Linear regression using standard deviations as regressors? | CC BY-SA 3.0 | null | 2011-05-08T22:23:20.810 | 2011-07-02T03:14:09.787 | 2011-05-09T00:18:46.427 | 919 | 221 | [
"regression",
"standard-deviation"
] |
10531 | 1 | 10612 | null | 6 | 932 | I'm wondering if this is possible to fit structural equation model for experimental design data.
Problem
Suppose a researcher observed four responses $Y_1$, $Y_2$, $Y_3$, and $Y_4$ along with three covariates $X_1$, $X_2$, and $X_3$ from an experiment involving ab treatment combinations from a fixed factor A with a lev... | Structural equation modeling for experimental design data | CC BY-SA 3.0 | null | 2011-05-08T23:04:11.983 | 2011-05-10T18:22:00.337 | 2011-05-09T14:01:51.513 | 3903 | 3903 | [
"mixed-model",
"experiment-design",
"structural-equation-modeling"
] |
10532 | 1 | 10572 | null | 6 | 1918 | Can someone tell a reference and/or book that explain how to use R for simulation of experimental design data?
| Reference or book on simulation of experimental design data in R | CC BY-SA 4.0 | null | 2011-05-08T23:13:44.127 | 2019-10-30T10:43:00.390 | 2019-10-30T10:43:00.390 | 11887 | 3903 | [
"r",
"references",
"experiment-design",
"simulation"
] |
10534 | 1 | null | null | 7 | 3185 | I have key-value pairs of text. The values can be multiple words (n-grams). For example,
```
A abcd
A efgh
B abcd
C wxyz
C mnop
```
I want to calculate [Pointwise Mutual Information](http://en.wikipedia.org/wiki/Pointwise_mutual_information) for the pairs. Is there a function in R to do this? Other... | Pointwise mutual information for text using R | CC BY-SA 3.0 | null | 2011-05-09T02:40:41.403 | 2011-10-03T09:55:17.947 | 2011-05-09T08:32:45.080 | null | 3111 | [
"r",
"text-mining",
"mutual-information"
] |
10535 | 1 | null | null | 4 | 1450 | I am having some difficulty understanding Adaboost.
How should the 1st threshold/classifier/weak learner be chosen?
It seems that there are two conditions which must be satisfied
- Choose the classifier with the lowest error
- $e(t)<0.5$ otherwise stop;
But if condition 1 is satisfied, doesn't it imply that conditi... | How to choose the 1st threshold/classifier/ weak learner in Adaboost? | CC BY-SA 3.0 | null | 2011-05-09T02:58:40.720 | 2012-02-06T12:09:33.973 | 2011-05-09T08:32:11.510 | null | 4527 | [
"machine-learning",
"boosting"
] |
10536 | 2 | null | 10478 | 0 | null | This does not answer your question, but: in a large data setting, it may be fine to tune the regularizer using a single train/test split, instead of doing it 10 or so times in cross-validation (or more for bootstrap). The size and representativeness of the sample chosen for the devset determines the accuracy of the es... | null | CC BY-SA 3.0 | null | 2011-05-09T03:45:30.610 | 2011-05-09T03:45:30.610 | null | null | 3799 | null |
10537 | 1 | null | null | 6 | 764 | I'm trying to fit some data using a hierarchical normal model
$y_i \sim N(\theta_i,\sigma^2)$
$\theta_i \sim N(\mu, \sigma_\theta^2)$
$(\mu,\sigma^2,\sigma_\theta^2) \sim diffuse$
I fit this model and I'm getting posteriors for $\sigma_\theta^2$ and $\sigma^2$ that are nearly identical. Is this an identifiability issu... | Possible identifiability issue in hierarchical model | CC BY-SA 3.0 | null | 2011-05-09T04:15:58.563 | 2011-06-30T01:13:53.170 | 2011-06-30T01:13:53.170 | 1499 | 4528 | [
"bayesian",
"multilevel-analysis",
"identifiability"
] |
10538 | 2 | null | 10537 | 5 | null | Your notation is a little strange (what do you mean by "diffuse"?), but I suspect that your prior on $\sigma^2_\theta$ is leading to an improper or nearly improper posterior, for one thing. See [here](http://stat.columbia.edu/~gelman/research/published/taumain.pdf) for a detailed exposition of just this model and appro... | null | CC BY-SA 3.0 | null | 2011-05-09T04:25:35.350 | 2011-05-22T04:32:25.327 | 2011-05-22T04:32:25.327 | 26 | 26 | null |
10539 | 1 | null | null | 25 | 15025 | migrated from [math.stackexchange](https://math.stackexchange.com/questions/37732/compute-approximate-percentiles-for-a-stream-of-integers-using-moments).
I'm processing a long stream of integers and am considering tracking a few moments in order to be able to approximately compute various percentiles for the stream wi... | Compute approximate quantiles for a stream of integers using moments? | CC BY-SA 3.0 | null | 2011-05-09T05:22:38.153 | 2017-02-27T09:39:27.020 | 2017-04-13T12:19:38.800 | -1 | 4530 | [
"algorithms",
"mathematical-statistics",
"moments"
] |
10540 | 1 | null | null | 47 | 102361 | Im trying to use silhouette plot to determine the number of cluster in my dataset. Given the dataset Train , i used the following matlab code
```
Train_data = full(Train);
Result = [];
for num_of_cluster = 1:20
centroid = kmeans(Train_data,num_of_cluster,'distance','sqeuclid');
s = silhouette(Train_dat... | How to interpret mean of Silhouette plot? | CC BY-SA 3.0 | null | 2011-05-09T06:05:22.237 | 2019-07-29T16:06:15.417 | 2011-05-09T06:43:41.717 | 930 | 4290 | [
"data-visualization",
"clustering",
"matlab"
] |
10542 | 2 | null | 9198 | 5 | null | That's an answer for question 2.
- STL: http://www.wessa.net/download/stl.pdf
- X-12-ARIMA (and much more): http://www.census.gov/srd/www/sapaper/sapaper.html
| null | CC BY-SA 3.0 | null | 2011-05-09T08:05:36.423 | 2017-06-14T21:18:41.800 | 2017-06-14T21:18:41.800 | 64672 | 1709 | null |
10543 | 1 | 10568 | null | 4 | 2061 | I've got a problem choosing the right model. I have a model with various variables (covariables and dummy variables). I was trying to find the best size for this model, so I first started by comparing different models with AIC. From this it followed, that the minimum AIC was reached when allowing all variables to stay ... | How to interpret decreasing AIC but higher standard errors in model selection? | CC BY-SA 3.0 | null | 2011-05-09T08:14:28.497 | 2011-05-09T19:07:23.040 | 2011-05-09T08:19:36.347 | 930 | 4496 | [
"model-selection",
"standard-error",
"aic"
] |
10544 | 1 | 10545 | null | 7 | 2242 | Let's say that N randomly chosen persons where asked a question where the answer could be in either of X categories. For example, 500 persons where asked which of the top 5 political parties they support the most. Each person can give only one answer.
How do I determine if the leading party which, for example, got 33 %... | Difference in means in multiple-choice poll | CC BY-SA 3.0 | null | 2011-05-09T08:38:08.217 | 2011-05-11T01:09:17.860 | null | null | 3401 | [
"statistical-significance",
"mean",
"polling"
] |
10545 | 2 | null | 10544 | 5 | null | Find out if there's any difference at all through [Pearson's Chi Square](http://en.wikipedia.org/wiki/Pearson%27s_chi-square_test). If this turns out significant, then do a (set of) post-hoc test(s), e.g. [Tukey's HSD](http://en.wikipedia.org/wiki/Tukey%27s_range_test).
| null | CC BY-SA 3.0 | null | 2011-05-09T08:55:17.227 | 2011-05-09T08:55:17.227 | null | null | 4257 | null |
10546 | 1 | null | null | 8 | 3766 | Let $T_1, T_2, \dots$ be iid sequence of exponential random variables with parameter $\lambda$. The sum $S_n = T_1 + T_2 + \dots + T_n$ is a Gamma distribution. Now as I understand the Poisson distribution is defined by $N_t$ as follows:
$$N_t = \max\{k: S_k \le t\}$$
How do I formally show that $N_t$ is a Poisson rand... | How to derive Poisson distribution from gamma distribution? | CC BY-SA 3.0 | null | 2011-05-09T09:05:18.130 | 2011-05-09T21:13:10.660 | 2011-05-09T12:17:35.457 | null | 862 | [
"distributions",
"probability",
"poisson-distribution",
"exponential-distribution",
"gamma-distribution"
] |
10548 | 2 | null | 10497 | 5 | null |
- You are not using Naive Bayes, you are actually using something I'd call "Multiplicative Decision Stump"-Classifer ;). You can do that, but I'd recommend in this case to calculate the micro or macro-average across all words in the sentence (instead of multiplying them). E.g. macro-average:
$p(Positive|sentence)=\fr... | null | CC BY-SA 3.0 | null | 2011-05-09T11:32:38.727 | 2011-05-09T19:59:17.390 | 2011-05-09T19:59:17.390 | 264 | 264 | null |
10549 | 2 | null | 10369 | 1 | null | The distribution of $Z_{i_{j}}$ is not difficult, and it is given by the Beta-F compound distribution:
$$p_{Z_{i_{j}}}(z)dz=\frac{n!}{(j-1)!(n-j)!} \frac{1}{\sigma_{z}}\phi(\frac{z}{\sigma_{z}})\left[\Phi(\frac{z}{\sigma_{z}})\right]^{j-1}\left[1-\Phi(\frac{z}{\sigma_{z}})\right]^{n-j}dz$$
Where $\phi(x)$ is a standard... | null | CC BY-SA 3.0 | null | 2011-05-09T12:27:32.203 | 2011-05-09T12:27:32.203 | null | null | 2392 | null |
10550 | 2 | null | 10532 | 4 | null | I have the feeling that pretty recent "[Introduction to Scientific Programming and Scientific Simulation Using R](http://rads.stackoverflow.com/amzn/click/1420068725)" by Owen Jones, Robert Maillardet, and Andrew Robinson (2009) could be what you are looking for.
There is also a very positive review for it [in the Jour... | null | CC BY-SA 3.0 | null | 2011-05-09T12:32:00.453 | 2011-05-09T12:32:00.453 | null | null | 442 | null |
10551 | 1 | 10552 | null | 8 | 9180 | I am having trouble determining what kernel I should use in a non-linear SVM without testing in advance. I want to know if there are any other ways to determine the best kernel without tests? How does it relate to the data?
| How do I choose what SVM kernels to use? | CC BY-SA 3.0 | null | 2011-05-09T13:01:52.487 | 2015-09-19T06:45:51.300 | 2015-09-19T06:45:51.300 | 87311 | 4531 | [
"svm",
"nonlinear-regression",
"kernel-trick"
] |
10552 | 2 | null | 10551 | 16 | null | Do your analysis with several different kernels. Make sure you cross-validate. Choose the kernel that performs the best during cross-validation and fit it to your whole dataset.
/edit: Here is some example code in R, for a classification SVM:
```
#Use a support vector machine to predict iris species
library(caret)
lib... | null | CC BY-SA 3.0 | null | 2011-05-09T14:21:32.587 | 2011-05-09T18:16:21.190 | 2011-05-09T18:16:21.190 | 2817 | 2817 | null |
10553 | 1 | null | null | 11 | 1843 | In G power 3, ANOVA repeated measures within-between interaction: Only the total sample size is reported assuming equal sample size for the two groups.
My questions are:
- How would it work if the sample sizes are slightly different, for example: N1/ N2 = 1.16.
- I have to input correlation between repeated measure... | How to use G Power 3 to calculate statistical power in mixed design ANOVA with unequal group sample sizes | CC BY-SA 3.0 | null | 2011-05-09T14:47:47.793 | 2011-06-08T15:44:08.497 | 2011-06-08T15:44:08.497 | 183 | 4453 | [
"repeated-measures",
"sample-size",
"statistical-power"
] |
10554 | 1 | 10566 | null | 7 | 870 | I'm working with dataset of individual households that I aggregate into 'areas' using several different spatial configurations, from smaller to bigger.
These areas are then characterized by four variables (two categorical, two continuous).
I'd like to see what effects these different aggregations have on the dataset. P... | Measuring homogeneity across different spatial aggregations of data | CC BY-SA 3.0 | null | 2011-05-09T15:00:34.937 | 2015-08-14T11:24:19.583 | 2015-08-14T11:24:19.583 | 11887 | 22 | [
"heteroscedasticity",
"spatial",
"aggregation",
"relative-distribution"
] |
10555 | 2 | null | 10359 | 3 | null | You can use Markov chains. You will have a to specify a density $p(x_t|x_{t-1})$. Of course you will have to be able to sample from that marginal. Then just sample...
| null | CC BY-SA 3.0 | null | 2011-05-09T15:45:40.490 | 2011-05-09T15:45:40.490 | null | null | 2860 | null |
10556 | 2 | null | 10532 | 4 | null | Here is an example of some code that I wrote for this purpose. The experimental design is: there are four levels of nitrogen and six replicates at each level. These data could be tested using a one-way ANOVA, but as the levels are continuous, I tested the fit of different curves.
```
set.seed(1)
library(nlme)
library(... | null | CC BY-SA 3.0 | null | 2011-05-09T15:46:54.257 | 2011-05-09T21:57:12.547 | 2011-05-09T21:57:12.547 | 1381 | 1381 | null |
10557 | 1 | null | null | 9 | 54920 | ```
names(mydat)[c(name)]<-c("newname")
```
From this, I know that the column/variable name "name" of the data frame mydat is replaced with "newname".
My question is if, I want to do this by a loop so that I will have some thing like:
newname1 newname2 newname3 newname4 and so on, how do I do it?
This is what did an... | How to change column names in data frame in R? | CC BY-SA 3.0 | null | 2011-05-09T16:18:23.433 | 2014-02-09T06:32:29.587 | 2011-05-11T15:33:27.243 | 183 | 4340 | [
"r"
] |
10558 | 2 | null | 9198 | 4 | null | If you are willing to learn to understand the diagnostics, X12-ARIMA provides a boatload of diagnostics that range from (ASCII) graphs to rule-of-thumb indicators. Learning and understanding the diagnostics is something of an education in time series and seasonal adjustment.
On the other hand, X12-ARIMA software is a o... | null | CC BY-SA 3.0 | null | 2011-05-09T16:23:21.067 | 2011-05-09T16:23:21.067 | null | null | 1764 | null |
10559 | 2 | null | 10517 | 10 | null | The short answer is that you can't.
The longer answer is that you really need to think about what you are trying to accomplish and what question(s) you are trying to answer.
Tests on distributions are not designed to prove a particular distribution, but to disprove (they are not perfect for that, you still have type I ... | null | CC BY-SA 3.0 | null | 2011-05-09T16:26:18.643 | 2011-05-09T16:26:18.643 | null | null | 4505 | null |
10560 | 2 | null | 10557 | 10 | null | Most obvious solution would be to change your code in for loop with the following:
```
names(mydat)[c(name)] <- paste("newname",i,sep="")
```
But you need to clarify what your variable `name` is. At the moment this loop will do 4 renames of the single column.
In general if the names which you want to change are in ... | null | CC BY-SA 3.0 | null | 2011-05-09T16:39:29.073 | 2011-05-10T06:05:35.363 | 2011-05-10T06:05:35.363 | 2116 | 2116 | null |
10561 | 2 | null | 10557 | 6 | null | Try using `sprintf` or `paste`, like this:
```
names(mydat)<-sprintf("name%d",1:10)
```
Also, note that the `names(mydat)[c(name)]` is a more-less a nonsense; `c(name)` is equivalent to writing just `name` and means "get the value of variable called `name`'; bracket will at least extract elements of `names(mydat)` but... | null | CC BY-SA 3.0 | null | 2011-05-09T16:40:24.673 | 2011-05-10T09:02:25.403 | 2011-05-10T09:02:25.403 | null | null | null |
10562 | 1 | 14073 | null | 7 | 1328 | I have a large distance matrix $3400\times 3400$.
I need to cluster them hierarchically and then cut the tree into clusters (like a partitional approach).
Which algorithm is most sensitive to finding natural clusters in the data based on the distance matrix?
How can I evaluate the result? I am planning on using averag... | Which hierarchical clustering algorithm? | CC BY-SA 3.0 | null | 2011-05-09T17:16:08.777 | 2011-08-10T05:20:23.550 | 2011-05-11T09:54:17.467 | 930 | 4534 | [
"clustering"
] |
10563 | 2 | null | 10517 | 6 | null | The only way to "prove" that data comes from a certain distribution (without an infinite number of samples) is to know precisely how that data is generated. For example, if you know that the data came from the magnitude of a circular bivariate normal random variable, it has a Rician distribution. Or if the data came ... | null | CC BY-SA 3.0 | null | 2011-05-09T17:17:21.243 | 2011-05-11T13:06:21.467 | 2011-05-11T13:06:21.467 | 3595 | 3595 | null |
10564 | 1 | null | null | 5 | 3699 | I ran a multivariate logistic regression with `glm` in `R` with some continuous and some categorical variables. Only continuous variable $A$ showed a p-value of < 0.05 and a confidence interval which did not stradle 1.
Running a Wilcoxon test (actually a Mann-Whitney test because the samples are not paired) with $A$ ... | Logistic regression and Wilcoxon test | CC BY-SA 3.0 | null | 2011-05-09T17:23:47.537 | 2017-04-03T15:49:25.863 | 2017-04-03T15:49:25.863 | 101426 | 2824 | [
"logistic",
"wilcoxon-mann-whitney-test"
] |
10565 | 2 | null | 10564 | 3 | null | The tests make different assumptions, and so do not give exactly the same result. The bigger problem is the (incorrect) assumption that failure to reject the null "indicates that there is no difference". It does not. It just means that you don't have enough evidence to reject the null of no difference.
| null | CC BY-SA 3.0 | null | 2011-05-09T17:39:12.920 | 2011-05-09T17:39:12.920 | null | null | 4506 | null |
10566 | 2 | null | 10554 | 7 | null | There are many ways you can characterize homogeneity, so there could be many answers to your question. One of the most intuitive ways I have seen it displayed is in a book chapter, "Spatial Analysis of Regional Income Inequality" by Sergio Rey in the book Spatially Integrated Social Science ([PDF](http://129.3.20.41/ep... | null | CC BY-SA 3.0 | null | 2011-05-09T17:45:34.507 | 2011-05-10T12:12:00.107 | 2011-05-10T12:12:00.107 | 1036 | 1036 | null |
10567 | 1 | 10573 | null | 8 | 3659 | I am currently looking at a cheminformatics problem where I am looking at the relationship between chemical structure and reactivity, e.g. how the angle at which two molecules approach each other affects the rate of the subsequent reaction. Obviously, the angle can only vary between 0° and 360°.
This is "quick check" q... | Can we use bounded continuous variables as predictors in regression and logistic regression? | CC BY-SA 3.0 | null | 2011-05-09T17:47:58.140 | 2013-09-05T09:45:23.387 | 2013-09-05T09:45:23.387 | 17230 | 4054 | [
"regression",
"logistic"
] |
10568 | 2 | null | 10543 | 4 | null | The AIC and standard error measure different things, and if you are trying to minimize standard error, a cross-validation approach may be better to use. Another alternative is the [Bayesian information criterion](http://en.wikipedia.org/wiki/Bayesian_information_criterion) (BIC), which is more parsimonious than the AI... | null | CC BY-SA 3.0 | null | 2011-05-09T17:52:57.150 | 2011-05-09T18:05:26.120 | 2011-05-09T18:05:26.120 | 930 | 3595 | null |
10570 | 2 | null | 10564 | 5 | null | Did you just fit one big glm model then look at the individual p-values?
Remember that those p-values are measuring the effect of that variable above and beyond all other variables in the model. It is possible that more of your covariates are really contributing, but there is redundant information, so they don't show ... | null | CC BY-SA 3.0 | null | 2011-05-09T18:03:19.990 | 2011-05-09T18:03:19.990 | null | null | 4505 | null |
10572 | 2 | null | 10532 | 4 | null | Statistical models in S, by Chambers and Hastie (Chapmann and Hall, 1991; or the so-called White Book), and to a lesser extent Modern Applied Statistics with S, by Venables and Ripley (Springer, 2002, 4th ed.), include some material about DoE and the analysis of common designs in S and R. Vikneswaran wrote [An R compan... | null | CC BY-SA 3.0 | null | 2011-05-09T18:28:15.963 | 2011-05-09T18:28:15.963 | null | null | 930 | null |
10573 | 2 | null | 10567 | 13 | null | The condition that dependent variables must be "continuous and unbounded" is unusual: there is no mathematical or statistical requirement for either.
In most regression models we posit that the dependent variable be a linear combination of the independent variables plus an independent random error term of zero mean, ap... | null | CC BY-SA 3.0 | null | 2011-05-09T18:33:42.420 | 2011-05-09T18:33:42.420 | null | null | 919 | null |
10574 | 1 | null | null | 8 | 3998 | I have two independent poisson random variables, $X_1$ and $X_2$, with $X_1 \sim \text{Pois}(\lambda_1)$ and $X_2 \sim \text{Pois}(\lambda_2)$. I want to test $H_0:\, \lambda_1 = \lambda_2$ versus the alternative $H_1:\, \lambda_1 \neq \lambda_2$.
I already derived maximum likelihood estimates under null and alternate ... | Power calculation for likelihood ratio test | CC BY-SA 3.0 | null | 2011-05-09T18:39:54.350 | 2011-05-09T20:18:48.010 | 2011-05-09T18:44:41.843 | 930 | 4098 | [
"poisson-distribution",
"statistical-power",
"likelihood-ratio"
] |
10576 | 2 | null | 10574 | 9 | null | You can do this using simulation.
Write a function that does your test and accepts the lambdas and sample size(s) as arguments (you have a good start above).
Now for a given set of lambdas and sample size(s) run the function a bunch of times (the replicate function in R is great for that). Then the power is just the p... | null | CC BY-SA 3.0 | null | 2011-05-09T19:07:42.993 | 2011-05-09T20:18:48.010 | 2011-05-09T20:18:48.010 | 4505 | 4505 | null |
10577 | 2 | null | 10546 | 6 | null | I'm sure that Durrett's proof is nice. A straight forward solution to the question asked is as follows.
For $n \geq 1$
$$
\begin{array}{rcl}
P(N_t = n) & = & \int_0^t P(S_{n+1} > t \mid S_n = s) P(S_n \in ds) \\
& = & \int_0^t P(T_{n+1} > t-s) P(S_n \in ds) \\
& = & \int_0^t e^{-\lambda(t-s)} \frac{\lambda^n s^{n-... | null | CC BY-SA 3.0 | null | 2011-05-09T19:53:46.250 | 2011-05-09T21:13:10.660 | 2011-05-09T21:13:10.660 | 4376 | 4376 | null |
10578 | 1 | null | null | 72 | 23141 | I am not comfortable with Fisher information, what it measures and how is it helpful. Also it's relationship with the Cramer-Rao bound is not apparent to me.
Can someone please give an intuitive explanation of these concepts?
| Intuitive explanation of Fisher Information and Cramer-Rao bound | CC BY-SA 3.0 | null | 2011-05-09T20:43:10.830 | 2019-11-14T18:08:19.120 | 2018-07-15T22:22:03.910 | 11887 | 4101 | [
"estimation",
"intuition",
"fisher-information"
] |
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