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9478 | 1 | null | null | 4 | 21420 | I have samples with each sample has n features, how to normalize these features to let feature values lie between interval [-1,1], please give a formula.
| How to normalize data to let each feature lie between [-1,1]? | CC BY-SA 3.0 | null | 2011-04-12T17:04:06.680 | 2015-04-01T09:19:18.187 | 2011-04-12T19:50:34.097 | null | 2141 | [
"normalization"
] |
9479 | 2 | null | 9315 | 22 | null | I'd try 'folding in'. This refers to taking one new document, adding it to the corpus, and then running Gibbs sampling just on the words in that new document, keeping the topic assignments of the old documents the same. This usually converges fast (maybe 5-10-20 iterations), and you don't need to sample your old corpus... | null | CC BY-SA 3.0 | null | 2011-04-12T17:17:44.110 | 2011-04-13T18:39:20.870 | 2011-04-13T18:39:20.870 | 3369 | 3369 | null |
9480 | 2 | null | 9477 | 22 | null | If you're willing to use [ggplot](http://had.co.nz/ggplot2/), you can try the following code.
With a continuous predictor
```
library(ggplot2)
gp <- ggplot(data=br, aes(x=tangle, y=gtangles))
gp + geom_point() + stat_smooth(method="lm", fullrange=T) + facet_grid(. ~ up)
```
for a facetted interaction plot
![enter ima... | null | CC BY-SA 3.0 | null | 2011-04-12T18:24:25.537 | 2011-04-20T20:02:55.400 | 2011-04-20T20:02:55.400 | 930 | 930 | null |
9481 | 2 | null | 7057 | 15 | null | In my experience, LARS is faster for small problems, very sparse problems, or very 'wide' problems (much much more features than samples). Indeed, its computational cost is limited by the number of features selected, if you don't compute the full regularization path. On the other hand, for big problems, glmnet (coordin... | null | CC BY-SA 4.0 | null | 2011-04-12T19:43:01.033 | 2021-09-24T05:02:58.787 | 2021-09-24T05:02:58.787 | 274906 | 1265 | null |
9482 | 1 | null | null | 2 | 248 | I am currently working with large datasets that have missing data points. My data ranges from the years 1979-2009. I want to choose, by year, the maximum value from that year. Missing values are replaced with a "."
I am currently using the formula:
{=MAX((E13:E2863=1979)*(H13:H2863))}
This array returns the max value ... | How do you choose MAX or MIN values from a range of incomplete data? | CC BY-SA 3.0 | null | 2011-04-12T20:24:51.287 | 2011-04-13T07:57:05.360 | 2011-04-13T07:57:05.360 | null | null | [
"modeling",
"excel"
] |
9483 | 1 | 9495 | null | 9 | 12011 | I have two datasets from genome-wide association studies. The only information available are the odd ratios and their confidence intervals (95%) for each genotyped SNP.
My want to generate a forest plot comparing these two odds ratios, but I can't find the way to calculate the combined confidence intervals to visualize... | How to calculate confidence intervals for pooled odd ratios in meta-analysis? | CC BY-SA 3.0 | null | 2011-04-12T20:56:40.753 | 2016-06-26T16:46:35.647 | 2011-04-13T08:25:08.687 | 930 | 4137 | [
"confidence-interval",
"meta-analysis",
"genetics",
"odds-ratio"
] |
9484 | 2 | null | 9483 | 0 | null | This is a comment (don't have enough rep. points). If you know the sample size (#cases and #controls) in each study, and the odds ratio for a SNP, you can reconstruct the 2x2 table of case/control by a/b (where a and b are the two alleles) for each of the two studies. Then you can just add those counts to get a table f... | null | CC BY-SA 3.0 | null | 2011-04-12T23:00:57.143 | 2011-04-12T23:00:57.143 | null | null | 3036 | null |
9485 | 2 | null | 9365 | 2 | null | An article with early impact regarding statistical bioinformatics research:
Jelizarow et al. [Over-optimism in bioinformatics: an illustration](http://bioinformatics.oxfordjournals.org/content/26/16/1990.abstract). Bioinformatics, 2010
It makes for an interesting discussion on bias sources, overfitting, and fishing for... | null | CC BY-SA 3.0 | null | 2011-04-13T01:35:39.070 | 2011-04-13T01:35:39.070 | null | null | 3770 | null |
9487 | 2 | null | 9482 | 2 | null | Using a Pivot Table isn't as quick or dirty, but may give you some more options for further analysis that make this approach worthwhile. I honestly have no idea how to convey in words how to use Excel's pivot tables, but if you highlight all of your data of interest and click on "insert --> pivot table" and then adjust... | null | CC BY-SA 3.0 | null | 2011-04-13T02:31:59.070 | 2011-04-13T02:31:59.070 | null | null | 696 | null |
9488 | 1 | 9489 | null | 0 | 171 |
### Question:
- Is it possible to get log liklihood values for my stepwise glms?
### Context:
I am able to get a logliklihood value using lmer with the following model. My study involves unbalanced repeated females, two sites (females don't exchange between sites), 8 predictors, and a response.
```
(glmfi... | How to get LogLiklihood value from logistic regression in R | CC BY-SA 3.0 | null | 2011-04-13T03:35:57.670 | 2011-04-13T03:51:10.630 | 2011-04-13T03:49:37.880 | 183 | 4027 | [
"r",
"likelihood-ratio"
] |
9489 | 2 | null | 9488 | 2 | null | Have you tried `logLik(lrfit1)`?
| null | CC BY-SA 3.0 | null | 2011-04-13T03:51:10.630 | 2011-04-13T03:51:10.630 | null | null | 1569 | null |
9490 | 1 | 9524 | null | 10 | 4948 | The Singular Value Decomposition (SVD) of a matrix is
$$A_{m\times n} = U_{m\times m}\Lambda_{m\times n} V_{n\times n}'$$
where $U$ and $V$ are orthogonal matrices and $\Lambda$ has (i, i) entry $\lambda_i \geq 0$ for $i = 1, 2, \cdots , min(m, n)$ and the other entries are zero. Then the left singular vectors $U$ fo... | Singular value decomposition of a three-dimensional array | CC BY-SA 3.0 | null | 2011-04-13T05:49:33.487 | 2011-04-13T15:51:38.890 | 2011-04-13T07:51:09.623 | null | 3903 | [
"svd"
] |
9491 | 1 | null | null | 15 | 548 | I came across the article by [Hervé Abdi](http://www.utdallas.edu/~herve/Abdi-SVD2007-pretty.pdf) about generalized SVD. The author mentioned:
>
The generalized SVD (GSVD) decomposes a rectangular matrix and takes into account constraints imposed on the rows and the columns of the matrix. The GSVD gives a weighted ge... | Does GSVD implement all linear multivariate techniques? | CC BY-SA 3.0 | null | 2011-04-13T06:10:47.197 | 2014-04-17T13:04:54.810 | 2011-09-22T08:42:55.030 | 3903 | 3903 | [
"multivariate-analysis",
"svd"
] |
9492 | 2 | null | 9477 | 12 | null | There's also Fox and Hong's effects package in R. See the J. Stat. Soft. papers [here](http://www.jstatsoft.org/v08/i15/paper) and [here](http://www.jstatsoft.org/v32/i01/paper) for examples with confidence intervals and generating R code.
It's not quite as pretty as a ggplot solution, but quite a bit more general, ... | null | CC BY-SA 3.0 | null | 2011-04-13T08:57:54.630 | 2011-04-13T08:57:54.630 | null | null | 1739 | null |
9493 | 1 | null | null | 3 | 135 | I have a software application which uses a queue and multiple processors to process those jobs. Jobs get re-run on a daily basis for customers, but we also have new customers signing up regularly.
The problem is that customers generally sign up during office hours, and the daily re-running of the jobs simply schedules ... | How can I even out a random distribution while minimising how far each data point is moved? | CC BY-SA 3.0 | null | 2011-04-13T09:42:14.907 | 2011-04-13T10:32:35.167 | 2011-04-13T10:32:35.167 | 449 | 4144 | [
"smoothing",
"randomness",
"queueing"
] |
9494 | 1 | null | null | 8 | 8436 | Currently I am working with Text Mining which includes sentiment identification and assigning corresponding business categories using open source tool R. I found these two documents which helped me to some extent:
- http://www.jstatsoft.org/v25/i05/
- http://epub.wu.ac.at/1923/1/document.pdf
My approach is to token... | How to perform text mining, sentiment mining, and business category identification, and where to obtain a categorization library | CC BY-SA 3.0 | null | 2011-04-13T10:01:19.413 | 2017-02-16T18:01:52.683 | 2011-04-13T11:34:00.200 | 183 | 4145 | [
"r",
"text-mining"
] |
9495 | 2 | null | 9483 | 10 | null | In most meta-analysis of odds ratios, the standard errors $se_i$ are based on the log odds ratios $log(OR_i)$. So, do you happen to know how your $se_i$ have been estimated (and what metric they reflect? $OR$ or $log(OR)$)? Given that the $se_i$ are based on $log(OR_i)$, then the pooled standard error (under a fixed ef... | null | CC BY-SA 3.0 | null | 2011-04-13T10:17:32.607 | 2011-04-14T12:44:16.130 | 2011-04-14T12:44:16.130 | 307 | 307 | null |
9496 | 2 | null | 9493 | 1 | null | This is a problem in optimal control. But you only need a few tools to get a practical solution for your problem.
1) a way to estimate the time distribution of jobs from new customers. Plotting the hourly, daily, and weekly averages for instances of jobs from new customers will give you a feel for the periodicity of ... | null | CC BY-SA 3.0 | null | 2011-04-13T10:23:21.593 | 2011-04-13T10:23:21.593 | null | null | 3567 | null |
9497 | 2 | null | 4802 | 4 | null | Queue models depend on a few key distributions: the distribution of the time gaps between incoming jobs, the distribution of service times (how long it takes to process a job). Some commonly used models for these distributions are the exponential, gamma, and Weibull distributions. To find out which distribution is ap... | null | CC BY-SA 3.0 | null | 2011-04-13T10:38:55.930 | 2011-04-13T10:38:55.930 | null | null | 3567 | null |
9499 | 1 | 9514 | null | 2 | 791 | I've just started playing with the R forecast package and found I must be doing something wrong because I can't get a decent prediction for a simple sinus.
```
weightData <- data.frame(weight = sin(seq(1:100)), week=1:100)
weight <- as.numeric(weightData$weight)
predicted <- forecast(weight,h=3,level=95)
# see the pr... | Forecast R package producing flat predictions | CC BY-SA 3.0 | null | 2011-04-13T10:55:07.987 | 2011-04-13T14:14:58.703 | null | null | 4134 | [
"r",
"forecasting"
] |
9500 | 1 | 9522 | null | 24 | 28584 | You can use the decathlon dataset {FactoMineR} to reproduce this. The question is why the computed eigenvalues differ from those of the covariance matrix.
Here are the eigenvalues using `princomp`:
```
> library(FactoMineR);data(decathlon)
> pr <- princomp(decathlon[1:10], cor=F)
> pr$sd^2
Comp.1 Comp.2 ... | Why do the R functions 'princomp' and 'prcomp' give different eigenvalues? | CC BY-SA 3.0 | null | 2011-04-13T10:57:05.660 | 2016-10-30T15:08:10.357 | 2015-02-07T21:46:36.967 | 28666 | 339 | [
"r",
"pca"
] |
9501 | 1 | 9576 | null | 12 | 10870 | Firstly, by analytically integrate, I mean, is there an integration rule to solve this as opposed to numerical analyses (such as trapezoidal, Gauss-Legendre or Simpson's rules)?
I have a function $\newcommand{\rd}{\mathrm{d}}f(x) = x g(x; \mu, \sigma)$ where
$$
g(x; \mu, \sigma) = \frac{1}{\sigma x \sqrt{2\pi}} e^{-\f... | Is it possible to analytically integrate $x$ multiplied by the lognormal probability density function? | CC BY-SA 3.0 | null | 2011-04-13T11:30:07.083 | 2011-04-15T02:50:14.760 | 2011-04-15T01:07:53.763 | 2970 | 4146 | [
"distributions",
"lognormal-distribution"
] |
9503 | 1 | null | null | 7 | 2993 | I am running a regression equation and I want to enter in 12 indepdendent variables then stepwise enter 7 more independent variables and not have an origin.
- DV is shfl.
- I want to enter in the following 12 independent dummy variables
ajan
bfeb
cmar
dapr
emay
fjun
gjul
haug
isep
joct
knov
ldec
- And then I wa... | Multiple regression with no origin and mix of directly entered and stepwise entered variables using R | CC BY-SA 3.0 | null | 2011-04-13T11:41:57.880 | 2011-04-13T13:43:37.057 | 2011-04-13T11:53:01.557 | 183 | 4148 | [
"r",
"stepwise-regression"
] |
9505 | 1 | 9543 | null | 3 | 297 | I am working on a real-time recommendation engine. At one step, I have a feature that resembles a string-encoded item set, so I took Jaccard on the tokenized string to get a good similarity result. Frankly, Jaccard offers great results, but it takes far too much time on runtime.
My current prototype environment for thi... | Item set similarity for real-time calculation purposes? | CC BY-SA 3.0 | null | 2011-04-13T12:07:18.300 | 2013-08-19T14:23:01.063 | 2013-08-19T14:23:01.063 | 22468 | 1158 | [
"recommender-system",
"java"
] |
9506 | 1 | 9516 | null | 28 | 27697 | I am new to R and to time series analysis. I am trying to find the trend of a long (40 years) daily temperature time series and tried to different approximations. First one is just a simple linear regression and second one is Seasonal Decomposition of Time Series by Loess.
In the latter it appears that the seasonal com... | STL trend of time series using R | CC BY-SA 3.0 | null | 2011-04-13T12:07:56.007 | 2015-09-21T18:24:48.010 | 2011-04-13T12:15:51.427 | 183 | 4147 | [
"r",
"time-series",
"trend"
] |
9507 | 1 | 9564 | null | 5 | 5932 | As a part of my studies, I’m trying to cluster co-occurrences of URLs and tags in data from Delicious. I found a promising method for this in a paper called “[Emergent Semantics from Folksonomies: A Quantitative Study](http://www.lambda.ee/images/9/93/Semanticsfolksonomies.pdf)” (pages 6-13). It used a Separable Mixtur... | How to initialize EM-algorithm when trying to fit data to a separable mixture model? | CC BY-SA 3.0 | null | 2011-04-13T12:39:58.633 | 2011-04-20T06:52:07.723 | 2011-04-15T08:15:01.263 | null | 4141 | [
"expectation-maximization"
] |
9508 | 1 | null | null | 4 | 728 | I'm analyzing the results of a hormone manipulation experiment. I measured a number of variables at three times in three groups. The groups are different sizes and not all individuals were measured every time, so I'm using GLMM rather than a repeated-measures ANOVA. I created the model then tested the significance of t... | Some doubts about using GLMM | CC BY-SA 3.0 | null | 2011-04-13T13:09:15.407 | 2011-07-17T18:18:19.500 | 2011-07-17T18:18:19.500 | null | 124 | [
"r",
"confidence-interval",
"mixed-model",
"repeated-measures",
"effect-size"
] |
9509 | 2 | null | 9483 | 3 | null | Actually, you could use software like [METAL](http://bioinformatics.oxfordjournals.org/content/26/17/2190.full) which is specifically designed for meta-analyses in GWA context.
It's awkward that plink doesn't give the confidence interval. However, you can get the CI because you have the final OR (take $\log(\text{OR})... | null | CC BY-SA 3.0 | null | 2011-04-13T13:20:03.047 | 2011-04-13T15:26:01.423 | 2011-04-13T15:26:01.423 | 930 | 3946 | null |
9510 | 1 | 9513 | null | 55 | 38208 | If I wanted to get the probability of 9 successes in 16 trials with each trial having a probability of 0.6 I could use a binomial distribution. What could I use if each of the 16 trials has a different probability of success?
| Probability distribution for different probabilities | CC BY-SA 3.0 | null | 2011-04-13T13:34:06.930 | 2015-07-02T04:33:14.487 | 2011-04-14T07:16:48.973 | null | 4150 | [
"distributions",
"probability",
"binomial-distribution"
] |
9511 | 2 | null | 9503 | 7 | null | I think you can set up your base model, that is the one with your 12 IVs and then use `add1()` with the remaining predictors. So, say you have a model `mod1` defined like `mod1 <- lm(y ~ 0+x1+x2+x3)` (`0+` means no intercept), then
```
add1(mod1, ~ .+x4+x5+x6, test="F")
```
will add and test one predictor after the ot... | null | CC BY-SA 3.0 | null | 2011-04-13T13:43:37.057 | 2011-04-13T13:43:37.057 | null | null | 930 | null |
9512 | 1 | null | null | 7 | 4518 | I have a time series data of 30 years and found that ARIMA(0,1,1) has best model among others. I have used the simulate.Arima (forecast package) function to simulate the series into the future.
```
library(forecast)
series <- ts(seq(25,55), start=c(1976,1))
arima_s <- Arima(series, c(0,1,1))
simulate(arima_s, nsim=5... | How to update ARIMA forecast in R? | CC BY-SA 3.0 | null | 2011-04-13T13:48:56.380 | 2014-08-24T14:22:54.270 | 2011-04-14T11:54:52.443 | null | 3084 | [
"r",
"time-series",
"forecasting",
"arima"
] |
9513 | 2 | null | 9510 | 31 | null | This is the sum of 16 (presumably independent) Binomial trials. The assumption of independence allows us to multiply probabilities. Whence, after two trials with probabilities $p_1$ and $p_2$ of success the chance of success on both trials is $p_1 p_2$, the chance of no successes is $(1-p_1)(1-p_2)$, and the chance o... | null | CC BY-SA 3.0 | null | 2011-04-13T14:03:30.150 | 2014-10-08T14:34:02.737 | 2014-10-08T14:34:02.737 | 919 | 919 | null |
9514 | 2 | null | 9499 | 3 | null | No automated forecasting method can produce good forecast for all data. If that was the case, the field of statistics would be for want of a better word dead. The package forecast picks the best exponential smoothing model for the given data. It works best with the certain class of time series data, which is not the ca... | null | CC BY-SA 3.0 | null | 2011-04-13T14:14:58.703 | 2011-04-13T14:14:58.703 | null | null | 2116 | null |
9515 | 2 | null | 8562 | 1 | null | Riffing off of Thomas' suggestion, I think a multilevel model for this data would look something like this...
y(hat) = TrialTypeA + TrialTypeB + ModalityA + ModalityB + TaskOrder + TrialTypeA:ModalityA + TrialTypeB:ModalityB + TrialTypeA:TaskOrder + TrialTypeB + TaskOrder
At a deeper layer in the model each of these va... | null | CC BY-SA 3.0 | null | 2011-04-13T14:22:25.767 | 2011-04-13T14:22:25.767 | null | null | 196 | null |
9516 | 2 | null | 9506 | 21 | null | I wouldn't bother with `stl()` for this - the bandwidth for the lowess smoother used to extract the trend is far, far, to small resulting in the small scale fluctuations you see. I would use an additive model. Here is an example using data and model code from Simon Wood's book on GAMs:
```
require(mgcv)
require(gamair)... | null | CC BY-SA 3.0 | null | 2011-04-13T14:26:48.023 | 2011-04-13T15:43:20.187 | 2011-04-13T15:43:20.187 | 1390 | 1390 | null |
9517 | 1 | 9521 | null | 4 | 562 | I work for a commission-based company that gives accounts to employees for about a month and the employees try and resolve the account, if they are successful they get a commission, otherwise the account goes to another employee to try and resolve.
We are running some reports to measure some performance characteristic... | Whether to use mean or median to summarise the central tendency of length of time to perform a task | CC BY-SA 3.0 | null | 2011-04-13T13:02:01.697 | 2011-04-13T15:19:35.777 | 2011-04-13T14:52:39.297 | 183 | 4170 | [
"mean"
] |
9519 | 1 | 9546 | null | 4 | 267 | I am creating a term to describe a design that may not be the proper term ("Staggered within subjects design"). What I mean by this is one can imagine a within subjects design with 3 levels. Each participant provides data for two levels, and between participant the order in which the data is collected is counter-bala... | Is there literature on staggered within subjects designs? What are the consequences of such a design? | CC BY-SA 3.0 | null | 2011-04-13T14:57:38.620 | 2011-04-14T06:50:16.403 | null | null | 196 | [
"anova",
"repeated-measures"
] |
9520 | 2 | null | 4473 | 4 | null | You use the example "January, February, and March", and I hope that's more for illustration and it isn't literally all the data you have. For monthly data, you really should have 3+ years of data, and places like the Census Bureau won't touch a monthly series with less than 7 years of data.
Also, you don't mention exac... | null | CC BY-SA 3.0 | null | 2011-04-13T15:01:29.147 | 2011-04-13T15:01:29.147 | null | null | 1764 | null |
9521 | 2 | null | 9517 | 5 | null | You should use the median, not the mean. However, you'll need to use methods appropriate for [time-to-event (survival)](http://en.wikipedia.org/wiki/Survival_analysis) data that deal appropriately with [censoring](http://en.wikipedia.org/wiki/Censoring_%28statistics%29): if the account was handled to another employee w... | null | CC BY-SA 3.0 | null | 2011-04-13T15:19:35.777 | 2011-04-13T15:19:35.777 | null | null | 449 | null |
9522 | 2 | null | 9500 | 18 | null | As pointed out in the comments, it's because `princomp` uses $N$ for the divisor, but `prcomp` and the direct calculation using `cov` both use $N-1$ instead of $N$.
This is mentioned in both the Details section of `help(princomp)`:
>
Note that the default calculation uses divisor 'N' for the covariance matrix.
and t... | null | CC BY-SA 3.0 | null | 2011-04-13T15:31:24.723 | 2016-10-30T15:08:10.357 | 2016-10-30T15:08:10.357 | 1657 | 1657 | null |
9523 | 2 | null | 9190 | 1 | null | [A Tour through the Visualization Zoo](http://queue.acm.org/detail.cfm?id=1805128) (Heer et al., Visualization
8(5) 2010) offers a particularly interesting overview of "innovative" and interactive techniques for displaying data.
On a related point, a good software for data visualization, including the aforementioned ... | null | CC BY-SA 3.0 | null | 2011-04-13T15:39:52.810 | 2011-04-13T15:39:52.810 | null | null | 930 | null |
9524 | 2 | null | 9490 | 10 | null | There are several notions of decomposition of such a tensor. Last year I asked [essentially the same question](http://www.mapleprimes.com/questions/97377-Decompose-A-Third-Order-Tensor-Into-Pure-Tensors) on the MaplePrimes site, answered it myself by referring to [wikipedia](http://en.wikipedia.org/wiki/Higher-order_si... | null | CC BY-SA 3.0 | null | 2011-04-13T15:51:38.890 | 2011-04-13T15:51:38.890 | null | null | 2898 | null |
9525 | 2 | null | 6949 | 5 | null | Fraud detection is a rare class problem. [Chapter Six of Charles Elkan's Notes](http://cseweb.ucsd.edu/~elkan/291/) for his Graduate Course in Data Mining and Predictive Analytics at UCSD walks you through the prediction of a rare class, and the pitfalls and proper ways to evaluate the success of such a model. The meth... | null | CC BY-SA 3.0 | null | 2011-04-13T17:16:56.247 | 2011-04-13T17:16:56.247 | null | null | 2166 | null |
9526 | 1 | null | null | 2 | 106 | I'm working on a project that will convert $USD to other currencies. The system will use average monthly exchange rates instead of daily because of pre-existing limitations. I need to calculate an estimate of the amount of error that will result from using monthly average. My idea is to
- Download historical daily ... | Calculate error for monthly exchange rates | CC BY-SA 3.0 | null | 2011-04-13T17:52:53.233 | 2011-04-15T08:18:51.293 | 2011-04-15T08:18:51.293 | null | 4154 | [
"estimation",
"standard-deviation"
] |
9527 | 2 | null | 9474 | 1 | null | Ha. It [looks like](http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1308339) this is an unsolved problem in applied statistics. The best MRC estimators execute in $n^2log(n)$ time or worse, so of course no code is available.
| null | CC BY-SA 3.0 | null | 2011-04-13T18:07:07.070 | 2011-04-13T18:07:07.070 | null | null | 4110 | null |
9528 | 2 | null | 9431 | 2 | null | You can either estimate a parametric model of the error using MLE, or you can use a semi-paramteric approach based on something like the maximal rank correlation (MRC) estimator. Computationally, MRC is prohibitive for large samples, so it looks like MLE is the right approach for me.
Thanks to GaBorgulya for some good... | null | CC BY-SA 3.0 | null | 2011-04-13T18:13:24.987 | 2011-04-13T18:13:24.987 | null | null | 4110 | null |
9532 | 1 | 13155 | null | 6 | 381 | This is a statistical version of my [Math.SE ](https://math.stackexchange.com/questions/30731/will-two-convex-hulls-overlap) post.
Given natural numbers $b$ and $r$, uniformly randomly choose $b+r$ points within a unit square. Call the $b$ points the blue points and the $r$ points red points. Let $p(b,r)$ be the proba... | Monte Carlo estimation of convex hull overlap probability | CC BY-SA 3.0 | 0 | 2011-04-13T21:09:57.260 | 2011-07-17T18:15:16.630 | 2017-04-13T12:19:38.853 | -1 | 4011 | [
"monte-carlo"
] |
9533 | 1 | null | null | 6 | 498 | I have 150 observations, 500 features, and I am interested in novelty detection (outlier detection): given a new observation (let's say 'patient') I want to know if it is different from the previous ones (let's call it 'control'). If I had a lot of data, I would probably be using statistical testing at the univariate p... | Learning a univariate transform (kernel?) for novelty detection | CC BY-SA 3.0 | null | 2011-04-13T21:38:03.710 | 2015-04-19T20:50:08.983 | 2015-04-19T20:50:08.983 | 9964 | 1265 | [
"machine-learning",
"outliers",
"kernel-trick"
] |
9534 | 2 | null | 9512 | 10 | null | Update:
It turns out that the Arima function has an argument for supplying old model:
```
adj_s <- Arima(series,model=arima_s)
```
The end result might be the same for both approaches, but I would advise using second one, because it clearly is tested more thoroughly.
**Old answer: **
As it happens, I encountered simi... | null | CC BY-SA 3.0 | null | 2011-04-13T21:54:17.267 | 2014-08-24T14:22:54.270 | 2014-08-24T14:22:54.270 | 2116 | 2116 | null |
9535 | 1 | 9538 | null | 33 | 22830 | I've run across a couple guides suggesting that I use R's nlm for maximum likelihood estimation. But none of them (including [R's documentation](http://stat.ethz.ch/R-manual/R-devel/library/stats/html/nlm.html)) gives much theoretical guidance for when to use or not use the function.
As far as I can tell, nlm is just ... | When should I *not* use R's nlm function for MLE? | CC BY-SA 3.0 | null | 2011-04-14T00:40:22.830 | 2012-10-11T20:41:35.183 | null | null | 4110 | [
"r",
"maximum-likelihood"
] |
9536 | 1 | 9554 | null | 4 | 3096 | I am sick of using the examples in the book. Is there an easy place to find data for which z-score/percentile/normal distribution stuff would be easy to see?
| Where can I find good publicly available data that I could use to teach z-scores to my college students? | CC BY-SA 3.0 | null | 2011-04-14T01:33:55.987 | 2013-11-07T12:41:24.940 | null | null | 1490 | [
"dataset"
] |
9537 | 2 | null | 9535 | 17 | null | When to use and not to use any particular method of maximization depends to a great extent on the type of data you have. `nlm` will work just fine if the likelihood surface isn't particularly "rough" and is everywhere differentiable. `nlminb` provides a way to constrain parameter values to particular bounding boxes. `o... | null | CC BY-SA 3.0 | null | 2011-04-14T02:27:08.703 | 2011-04-14T02:27:08.703 | null | null | 3265 | null |
9538 | 2 | null | 9535 | 47 | null | There are a number of general-purpose optimization routines in base R that I'm aware of: `optim`, `nlminb`, `nlm` and `constrOptim` (which handles linear inequality constraints, and calls `optim` under the hood). Here are some things that you might want to consider in choosing which one to use.
- optim can use a numbe... | null | CC BY-SA 3.0 | null | 2011-04-14T03:00:07.563 | 2011-04-14T03:00:07.563 | null | null | 1569 | null |
9539 | 1 | null | null | 1 | 123 | I'm familiar with the diagnostics required for OLS, however I'm in new territory with a model I'm fitting to data in R, using Poisson regression with GLM.
What are the standard methods in evaluating a WLS model?
| How do I go about conducting model diagnostics on WLS? | CC BY-SA 3.0 | null | 2011-04-14T03:20:16.033 | 2021-05-14T16:57:27.933 | 2021-05-14T16:57:27.933 | 11887 | 1965 | [
"r",
"modeling",
"poisson-regression",
"diagnostic"
] |
9540 | 2 | null | 7164 | 3 | null | The generalization of the change of variable formula to the non-bijective case is generally hard to write out explicitly, check [http://en.wikipedia.org/wiki/Probability_density_function#Multiple_variables](http://en.wikipedia.org/wiki/Probability_density_function#Multiple_variables)
which essentially formalizes mpikta... | null | CC BY-SA 3.0 | null | 2011-04-14T04:00:01.310 | 2011-04-14T04:00:01.310 | null | null | null | null |
9541 | 1 | null | null | 1 | 1563 | I am trying to determine model significance using:
```
1-pchisq(null deviance-residual deviance, null df- residual df)
```
I have 5 models:
- Four models were estimated with GLMs, which gave me null and residual DFs in the summary.
- The fifth model was estimated with the lmer function because of the nested structu... | How can I obtain null and residual deviance/degrees of freedom for assessing model significance? | CC BY-SA 3.0 | null | 2011-04-14T04:13:36.247 | 2011-06-18T15:00:41.607 | 2011-04-19T14:30:05.650 | 930 | 4027 | [
"r",
"statistical-significance",
"degrees-of-freedom"
] |
9542 | 1 | 14883 | null | 30 | 22400 | I know that in a regression situation, if you have a set of highly correlated variables this is usually "bad" because of the instability in the estimated coefficients (variance goes toward infinity as determinant goes towards zero).
My question is whether this "badness" persists in a PCA situation. Do the coefficients... | Is PCA unstable under multicollinearity? | CC BY-SA 3.0 | null | 2011-04-14T04:51:15.753 | 2011-08-27T17:07:07.827 | 2011-04-14T07:19:10.440 | null | 2392 | [
"pca",
"multicollinearity"
] |
9543 | 2 | null | 9505 | 2 | null | You can use [MinHashing](http://en.wikipedia.org/wiki/MinHash) to get a fast approximate jacard similiarity match for your current item set against a database of existing of item sets.
You might use a few min hashes to find quickly find candidate recommendations, and only do the full jacard computation against only th... | null | CC BY-SA 3.0 | null | 2011-04-14T05:53:49.233 | 2011-04-14T05:53:49.233 | null | null | 4164 | null |
9544 | 1 | 9563 | null | 7 | 1404 | Let $A\in\mathbb{R}^{n \times n}$ be a dense symmetric positive-definite matrix (the $X^TX$ from [here](https://stats.stackexchange.com/questions/9341/regularized-fit-from-summarized-data)) and $b$ a vector in $\mathbb{R}^n$.
I need to compute $A^{-1}b$.
Two questions:
- Could you recommend an efficient and numericall... | Computing $(X^TX)^{-1}X^Ty$ in OLS | CC BY-SA 3.0 | null | 2011-04-14T05:58:16.167 | 2011-05-12T12:01:23.310 | 2017-04-13T12:44:33.357 | -1 | 439 | [
"regression",
"least-squares",
"matrix-inverse"
] |
9545 | 2 | null | 9510 | 15 | null | One alternative to @whuber's normal approximation is to use "mixing" probabilities, or a hierarchical model. This would apply when the $p_i$ are similar in some way, and you can model this by a probability distribution $p_i\sim Dist(\theta)$ with a density function of $g(p|\theta)$ indexed by some parameter $\theta$. ... | null | CC BY-SA 3.0 | null | 2011-04-14T06:48:46.820 | 2013-12-01T03:18:23.493 | 2013-12-01T03:18:23.493 | 2392 | 2392 | null |
9546 | 2 | null | 9519 | 2 | null | I'd probably call this a [cross-over design](http://en.wikipedia.org/wiki/Crossover_design) with three treatments and two periods, although you could also think of it as a [balanced incomplete block design](http://en.wikipedia.org/wiki/Incomplete_block_design) with three treatments and 'participant' as the blocking fac... | null | CC BY-SA 3.0 | null | 2011-04-14T06:50:16.403 | 2011-04-14T06:50:16.403 | null | null | 449 | null |
9547 | 1 | null | null | 2 | 1329 |
- When measuring the quantization error of a clustering, should the distance between samples/centroid be squared or not? I found both variants in the literature.
- Furthermore, is (squared) quantization error not the same as squared sum of errors?
| Measuring quantization error for clustering - squared or not? | CC BY-SA 3.0 | null | 2011-04-14T07:54:22.887 | 2011-04-14T13:47:33.077 | 2011-04-14T07:59:37.813 | 183 | null | [
"clustering"
] |
9548 | 2 | null | 9536 | 2 | null | One good website where you can find data for different disciplines.
[Rob Hyndman's Time Series Data library](http://robjhyndman.com/TSDL/)
| null | CC BY-SA 3.0 | null | 2011-04-14T09:38:51.977 | 2011-04-14T10:48:29.207 | 2011-04-14T10:48:29.207 | 183 | 3084 | null |
9549 | 1 | null | null | 8 | 3922 | Assume you have a class of approximately 800 students and following a set of assessments each student has a raw grade.
- How should these raw grades be converted into a final grade?
- Is it a good idea to scale the raw grades to a normal distribution?
| Should grades be assigned to students based on a normal distribution? | CC BY-SA 3.0 | null | 2011-04-14T09:43:45.847 | 2014-08-12T09:16:02.363 | 2011-04-14T10:41:27.343 | 183 | 4167 | [
"normal-distribution"
] |
9550 | 1 | null | null | 1 | 497 | I've got more than 20 (10 point likert scale) variables with more than 1000 entries each. What I want to do is compare the means of the answers on the questions.
A one-way anova seems suitable for this, but you can only categorize by the values of a variabele. I want to categorize by question, the variable itself.
Is t... | Compare means of different variables | CC BY-SA 3.0 | null | 2011-04-14T10:10:03.263 | 2011-04-14T10:34:50.687 | null | null | 4168 | [
"anova",
"spss"
] |
9551 | 2 | null | 9544 | 5 | null | The standard answer to your first question is Cholesky decomposition. To quote [the Wikipedia article](http://en.wikipedia.org/wiki/Cholesky_decomposition#Applications):
>
If $A$ is symmetric and positive definite, then we can solve $Ax = b$ [for $x$] by first computing the Cholesky decomposition $A = LL^\mathrm{T}$, ... | null | CC BY-SA 3.0 | null | 2011-04-14T10:32:32.233 | 2011-04-14T10:41:05.347 | 2011-04-14T10:41:05.347 | 449 | 449 | null |
9552 | 2 | null | 9550 | 4 | null |
- If the same 1000 participants answered each question:
consider using paired samples t-tests and repeated measures ANOVAs
- If a different 1000 participants answered each question:
then it sounds like you need to restructure your data file to conform to the expectations of the statistical package you are using.
... | null | CC BY-SA 3.0 | null | 2011-04-14T10:34:50.687 | 2011-04-14T10:34:50.687 | null | null | 183 | null |
9553 | 2 | null | 9542 | 3 | null | PCA is often a means to an ends; leading up to either inputs to a multiple regression or for use in a cluster analysis. I think in your case, you are talking about using the results of a PCA to perform a regression.
In that case, your objective of performing a PCA is to get rid of mulitcollinearity and get orthogonal i... | null | CC BY-SA 3.0 | null | 2011-04-14T10:44:19.680 | 2011-04-14T10:57:59.350 | 2011-04-14T10:57:59.350 | 930 | 3805 | null |
9554 | 2 | null | 9536 | 3 | null | You may wish to read answers to this existing question on [freely available datasets](https://stats.stackexchange.com/questions/7/locating-freely-available-data-samples).
In general, I imagine that you'd want a dataset with some interesting metric variables.
In psychology research methods classes that I've taught, we'v... | null | CC BY-SA 3.0 | null | 2011-04-14T10:55:13.367 | 2011-04-14T10:55:13.367 | 2017-04-13T12:44:40.807 | -1 | 183 | null |
9555 | 2 | null | 9544 | 6 | null | To add to @onestop's answer, another efficient way is to use [QR decomposition](http://en.wikipedia.org/wiki/QR_decomposition). The added benefit is that QR decomposition can be applied directly to $X$, and not to $X^TX$.
I think the QR decomposition can be made to work for your second question, it is definitely strai... | null | CC BY-SA 3.0 | null | 2011-04-14T10:57:09.693 | 2011-05-12T12:01:23.310 | 2011-05-12T12:01:23.310 | 830 | 2116 | null |
9556 | 1 | null | null | 3 | 463 | I have 2 genes (tf1 and tf2), which are affecting a third gene (tg). By affecting a gene I mean the changes in the value of tf1 and tf2 changes the value of tg. what we measure in the whole experiment is this value. We want to see if the values of tf1 and tf2 are dependent (which means they are regulating each other) a... | Interpretation of 3-way ANOVA | CC BY-SA 3.0 | null | 2011-04-14T11:20:00.523 | 2017-11-30T12:50:00.897 | 2011-04-28T17:27:47.293 | 2885 | 2885 | [
"anova",
"genetics",
"interpretation",
"bioinformatics",
"biostatistics"
] |
9557 | 1 | 9558 | null | 10 | 8988 | I was recently exposed to some statistical hypothesis testing methods (e.g. Friedman test) at work, and I would like to increase my knowledge on the topic.
Can you suggest a good introduction to statistical significance / statistical hypothesis testing for a computer scientist?
I am thinking of a PDF book or similar, ... | What is a good introduction to statistical hypothesis testing for computer scientists? | CC BY-SA 3.0 | null | 2011-04-14T12:07:36.113 | 2011-06-29T19:35:06.853 | 2011-04-14T12:17:05.553 | 4169 | 4169 | [
"hypothesis-testing",
"statistical-significance",
"p-value"
] |
9558 | 2 | null | 9557 | 6 | null | [http://greenteapress.com/thinkstats/](http://greenteapress.com/thinkstats/)
This seems like it would be useful for you.
Full disclosure: I have not read it, but I am working my way through the Think Like a Computer Scientist in Java, and am finding that extremely useful.
| null | CC BY-SA 3.0 | null | 2011-04-14T12:19:03.930 | 2011-04-14T12:19:03.930 | null | null | 656 | null |
9559 | 2 | null | 9549 | 6 | null | Why should grades be normally distributed?
Sometimes they are but if the grades are not normally distributed then the bell curve grading system, where the middle say 70% get C's, is probably not a good one to base grades off of. Although that grading is pretty harsh, few instructors would actually do it.
Use distribut... | null | CC BY-SA 3.0 | null | 2011-04-14T12:54:08.067 | 2011-04-14T12:54:08.067 | null | null | 2310 | null |
9560 | 2 | null | 9547 | 3 | null | The point of the squared error is that it results out of the underlying assumption, that your data is distributed with a Gaussian random component. (Like noise on your measurements, e.g.)
The sum of squares error comes from the log probability. Say your points are distributed according to $p$, then you want to pick you... | null | CC BY-SA 3.0 | null | 2011-04-14T13:47:33.077 | 2011-04-14T13:47:33.077 | null | null | 2860 | null |
9561 | 1 | 9569 | null | 35 | 38670 | This is an elementary question, but I wasn't able to find the answer. I have two measurements: n1 events in time t1 and n2 events in time t2, both produced (say) by Poisson processes with possibly-different lambda values.
This is actually from a news article, which essentially claims that since $n_1/t_1\neq n_2/t_2$ t... | Checking if two Poisson samples have the same mean | CC BY-SA 3.0 | null | 2011-04-14T14:26:53.683 | 2014-11-11T13:41:53.107 | null | null | 1378 | [
"hypothesis-testing",
"poisson-distribution"
] |
9562 | 2 | null | 9533 | 4 | null | Your setting is pretty hard. I have no solution, but a couple of points.
- Energy based models can give you a scalar corresponding to a "grade of belief" that an input is generated by the distribution of your data. It comes down to chosing a model and a good loss function. Check out Yann Lecun's tutorial on energy bas... | null | CC BY-SA 3.0 | null | 2011-04-14T14:28:33.387 | 2011-04-14T14:28:33.387 | null | null | 2860 | null |
9563 | 2 | null | 9544 | 5 | null | Regarding your second question, here is a way to do this for $n=i$, for simplicity of notation. Let $\alpha = A_{nn}, \, a = (A_{1n},\dots, A_{n-1,n})^T$ and therefore
$$ A = \begin{pmatrix} \tilde A & a \\ a^T & \alpha \end{pmatrix}
$$
Also let $A^{-1}$ be partitioned in the same way,
$$ A^{-1} = \begin{pmatrix} \til... | null | CC BY-SA 3.0 | null | 2011-04-14T14:34:05.890 | 2011-04-14T14:34:05.890 | null | null | 4062 | null |
9564 | 2 | null | 9507 | 5 | null | Whenever I implement a new algorithm, I get myself an easy, interpretable dataset on which I can try it out. This has several advantages, for example runtime (use a small dataset) or visualization (make things you want to plot have dimension 2 or 3).
Of course the behavior you see could result from the dataset. It feel... | null | CC BY-SA 3.0 | null | 2011-04-14T14:35:38.870 | 2011-04-14T14:35:38.870 | null | null | 2860 | null |
9566 | 1 | null | null | 11 | 2105 | I have the total number of calls received each week and have plotted them on a chart, going back nearly 3 years.
By eye it seems that there was a massive drop over Christmas, that doesn't seem to have recovered, it seems that there has been a step change in requests.
Is there a test I can do that can quantify this diff... | Determining if change in a time series is statistically significant | CC BY-SA 3.0 | null | 2011-04-14T14:48:57.507 | 2011-04-16T01:50:04.197 | 2011-04-15T03:54:14.787 | 183 | 4171 | [
"time-series",
"statistical-significance",
"change-point"
] |
9567 | 2 | null | 9561 | 11 | null | You're looking for a quick and easy check.
Under the null hypothesis that the rates (lambda values) are equal, say to $\lambda$, then you could view the two measurements as observing a single process for time $t = t_1+t_2$ and counting the events during the interval $[0, t_1]$ ($n_1$ in number) and the events during th... | null | CC BY-SA 3.0 | null | 2011-04-14T14:56:48.807 | 2011-04-14T14:56:48.807 | null | null | 919 | null |
9569 | 2 | null | 9561 | 29 | null | To test the Poisson mean, the conditional method was proposed by Przyborowski and Wilenski (1940). The conditional distribution of X1 given X1+X2 follows a binomial distribution
whose success probability is a function of the ratio two lambda. Therefore,
hypothesis testing and interval estimation procedures can be readi... | null | CC BY-SA 3.0 | null | 2011-04-14T14:59:25.827 | 2011-04-14T14:59:25.827 | null | null | 3084 | null |
9570 | 2 | null | 9566 | 11 | null | A very similar example is used in the tutorial of PyMC. If you assume that the daily amount of requests was constant until some point in time (maybe exactly Christmas) and after that it was constant again, all you need to do is substitute the numbers in the example: [http://pymc.googlecode.com/svn/doc/tutorial.html](ht... | null | CC BY-SA 3.0 | null | 2011-04-14T19:29:37.493 | 2011-04-16T01:50:04.197 | 2011-04-16T01:50:04.197 | 3911 | 3911 | null |
9571 | 2 | null | 9561 | 5 | null | I would be more interested in a confidence interval than a p value, here is a bootstrap approximation.
Calculating the lengths of the intervals first, and a check:
```
Lrec = as.numeric(as.Date("2010-07-01") - as.Date("2007-12-02")) # Length of recession
Lnrec = as.numeric(as.Date("2007-12-01") - as.Date("2001-12-01"))... | null | CC BY-SA 3.0 | null | 2011-04-14T20:09:55.573 | 2011-04-16T01:47:49.140 | 2011-04-16T01:47:49.140 | 3911 | 3911 | null |
9572 | 2 | null | 8007 | 1 | null | If you are interested in the amount of time it takes to complete an order, it seems that a duration analysis (aka survival or event history analysis) would be most appropriate. See the Wikipedia entry for an overview:
[http://en.wikipedia.org/wiki/Survival_analysis](http://en.wikipedia.org/wiki/Survival_analysis)
This ... | null | CC BY-SA 3.0 | null | 2011-04-14T20:58:55.363 | 2011-04-14T20:58:55.363 | null | null | 3265 | null |
9573 | 1 | 9575 | null | 114 | 195079 | Long ago I learnt that normal distribution was necessary to use a two sample T-test. Today a colleague told me that she learnt that for N>50 normal distribution was not necessary. Is that true?
If true is that because of the central limit theorem?
| T-test for non normal when N>50? | CC BY-SA 3.0 | null | 2011-04-14T21:55:43.747 | 2022-07-18T22:26:17.110 | 2021-07-29T11:58:51.467 | 301448 | 4176 | [
"hypothesis-testing",
"normal-distribution",
"t-test",
"inference",
"central-limit-theorem"
] |
9574 | 2 | null | 4111 | 4 | null | Mobile phone providers can count the number of phones in the area. Having an estimate of the mean number of phones/person good approximation can be calculated. This looks simple, so I assume it is in practice.
| null | CC BY-SA 3.0 | null | 2011-04-14T23:19:26.933 | 2011-04-14T23:19:26.933 | null | null | 3911 | null |
9575 | 2 | null | 9573 | 121 | null | Normality assumption of a t-test
Consider a large population from which you could take many different samples of a particular size. (In a particular study, you generally collect just one of these samples.)
The t-test assumes that the means of the different samples are normally distributed; it does not assume that the p... | null | CC BY-SA 3.0 | null | 2011-04-15T01:07:12.330 | 2015-11-25T04:03:52.120 | 2015-11-25T04:03:52.120 | 7290 | 3874 | null |
9576 | 2 | null | 9501 | 16 | null | Short answer: No, it is not possible, at least in terms of elementary functions. However, very good (and reasonably fast!) numerical algorithms exist to calculate such a quantity and they should be preferred over any numerical integration technique in this case.
Quantity of interest in terms of normal cdf
The quantity ... | null | CC BY-SA 3.0 | null | 2011-04-15T01:36:14.320 | 2011-04-15T02:50:14.760 | 2017-04-13T12:44:20.730 | -1 | 2970 | null |
9577 | 1 | null | null | 10 | 1383 | I have fit two generalized estimating equation (GEE) models to my data:
1) Model 1: Outcome is longitudinal Yes/No variable (A) (year 1,2,3,4,5) with longitudinal continuous predictor (B) for years 1,2,3,4,5.
2) Model 2: Outcome is the same longitudinal Yes/No variable (A), but now with my predictor fixed at its year ... | How can I assess GEE/logistic model fit when covariates have some missing data? | CC BY-SA 3.0 | null | 2011-04-15T02:39:43.933 | 2016-10-11T17:26:46.970 | 2011-04-15T08:17:00.480 | null | 4054 | [
"logistic",
"generalized-estimating-equations"
] |
9578 | 2 | null | 9573 | 6 | null | In my experience with just the one-sample t-test, I have found that the skew of the distributions is more important than the kurtosis, say. For non-skewed but fat-tailed distributions (a t with 5 degrees of freedom, a Tukey h-distribution with $h=0.24999$, etc), I have found that 40 samples has always been sufficient t... | null | CC BY-SA 3.0 | null | 2011-04-15T03:20:49.997 | 2011-04-15T18:30:54.513 | 2011-04-15T18:30:54.513 | 795 | 795 | null |
9579 | 2 | null | 8271 | 2 | null | I am guessing that you have your data in wide format.
This seems to be causing you confusion because in wide format it is less obvious that "time" is your second independent variable.
One option in SPSS for doing what it sounds like you want to do:
- Analyze -- GLM -- Repeated Measures
- Enter time as repeated measur... | null | CC BY-SA 3.0 | null | 2011-04-15T03:40:14.243 | 2011-04-15T03:50:06.243 | 2011-04-15T03:50:06.243 | 183 | 183 | null |
9580 | 2 | null | 9573 | 21 | null | See my previous answer to a question on the [robustness of the t-test](https://stats.stackexchange.com/questions/1386/robust-t-test-for-mean/1391#1391).
In particular, I recommend playing around with the [onlinestatsbook applet](http://onlinestatbook.com/stat_sim/robustness/index.html).
The image below is based on the ... | null | CC BY-SA 3.0 | null | 2011-04-15T07:23:36.947 | 2015-10-30T09:19:25.873 | 2017-04-13T12:44:37.583 | -1 | 183 | null |
9581 | 1 | null | null | 1 | 3627 | I have a huge dataset which contains 20 columns and many rows.
I have done clustering in SAS, Knime and SPSS, but I am new to R.
I have to do clustering on my dataset.
I have imported my data into R.
- What are some suggestions for getting started with cluster analysis in R?
| Getting started with cluster analysis in R | CC BY-SA 3.0 | null | 2011-04-15T11:07:26.733 | 2011-04-15T14:11:57.157 | 2011-04-15T11:45:53.927 | 183 | null | [
"r",
"clustering"
] |
9583 | 2 | null | 9581 | 4 | null | A lot of people coming from SAS or SPSS to R find the [Quick-R website useful](http://www.statmethods.net/).
There is a page on [cluster analysis](http://www.statmethods.net/advstats/cluster.html) which you may find useful in getting you started.
| null | CC BY-SA 3.0 | null | 2011-04-15T11:41:37.817 | 2011-04-15T14:11:57.157 | 2011-04-15T14:11:57.157 | 183 | 183 | null |
9584 | 2 | null | 9581 | 16 | null | ```
## dummy data
require(MASS)
set.seed(1)
dat <- data.frame(mvrnorm(100, mu = c(2,6,3),
Sigma = matrix(c(10, 2, 4,
2, 3, 0.5,
4, 0.5, 2), ncol = 3)))
```
So my data are in object `dat`, you have... | null | CC BY-SA 3.0 | null | 2011-04-15T12:10:43.937 | 2011-04-15T12:10:43.937 | null | null | 1390 | null |
9586 | 1 | null | null | 10 | 1924 | Excuse what may be an obvious question about bootstrapping. I got sucked in the Bayesian world early and never really explored bootstrapping as much as I should have.
I ran across an analysis in which the authors were interested in a survival analysis related to some time to failure data. They had about 100 points a... | Bootstrap confidence intervals on parameters or on distribution? | CC BY-SA 3.0 | null | 2011-04-15T14:47:27.237 | 2012-02-24T19:41:14.713 | null | null | 3591 | [
"confidence-interval",
"bootstrap"
] |
9587 | 1 | null | null | 2 | 975 | Adapted from my [previous, unanswered question](https://stats.stackexchange.com/questions/9508/glmm-questions-of-appropriateness-post-hoc-tests-effects-size-and-confidence):
I'm analyzing the results of a hormone manipulation experiment. I measured a number of variables at three times in three groups. The groups are di... | GLMM - test of significance | CC BY-SA 3.0 | null | 2011-04-15T15:13:03.293 | 2011-07-17T10:19:58.217 | 2017-04-13T12:44:29.013 | -1 | 124 | [
"r",
"mixed-model"
] |
9588 | 1 | null | null | 5 | 303 | I'm not really a statistician, but rather in need of statistical guidance, so I hope this is not too much of an off-topic question.
I'm writing a master's thesis (computational linguistics/NLP), and I've got several result sets I'm comparing. Now, I didn't really formulate a null and an alternative hypothesis before I ... | After the fact hypothesis testing | CC BY-SA 3.0 | null | 2011-04-15T15:32:24.263 | 2011-04-16T00:10:23.233 | null | null | 4185 | [
"hypothesis-testing"
] |
9589 | 2 | null | 9588 | 2 | null | It's not necessarily a problem that you didn't formulate hypotheses before running the study, but you may be doing a post-hoc analysis, which would be relevant. Also consider whether what your tests mean.
The population
I feel the need to point out that the population is sort of bizarre in this situation. If I understa... | null | CC BY-SA 3.0 | null | 2011-04-15T17:22:47.937 | 2011-04-15T17:22:47.937 | null | null | 3874 | null |
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