similar to: FW:

Hi, I' am doing a stats project using R to work out the size of a t-test and wilcoxon test depending on the distribution and sample size. I just can't get it to work - I want to put my results from the function size() into an array.At the moment I keep getting the error message:Error in res[distribution, test, samplesize] <- results : subscript out of boundsCan anyone tell me where

Hi, I'm trying to get better at things like lapply but it still stumps me. I have a function I've written, tested and debugged using individual calls to the function, ala: ResultList5 = DoAvgCalcs(IndexData, Lookback=5, SampleSize=TestSamples , Iterations=TestIterations ) ResultList8 = DoAvgCalcs(IndexData, Lookback=8, SampleSize=TestSamples , Iterations=TestIterations ) ResultList13

Here is the function that makes the data.frames in the list: funweek <- function(df) if (length(df$elapsed_time) > 5) { res = fitdist(df$elapsed_time,"exp") year = df$sale_year[1] sample = df$sale_week[1] mid = df$m_id[1] estimate = res$estimate sd = res$sd samplesize = res$n loglik = res$loglik aic = res$aic bic = res$bic chisq =

I am trying to use R to do loglogistic hazard estimation. My plan is to generate a loglogistic hazard sample data and then use survreg to estimate it. If everything is correct, survreg should return the parameters I have used to generate the sample data. I have written the following code to do a time invariant hazard estimation. The output of summary(modloglog) shows the factor loading of

Hi Hugo, I've been able to replicate your bug, including for other distributions (runif, rexp, rgamma, etc) which shouldn't be surprising since they're probably all drawing from the same pseudo-random number generator. ?Interestingly, it does not seem to depend on the choice of seed, I am not sure why that is the case. I'll point out first of all that the R-devel mailing list is

Hi Hugo, I've been able to replicate your bug, including for other distributions (runif, rexp, rgamma, etc) which shouldn't be surprising since they're probably all drawing from the same pseudo-random number generator. ?Interestingly, it does not seem to depend on the choice of seed, I am not sure why that is the case. I'll point out first of all that the R-devel mailing list is

I am transitioning from SAS to R and am struggling with a relatively simple analysis. Have tried Venables and Ripley and other guides but can't find a solution. I have an experiment with 12 tanks. Each tank holds 10 fish. The 12 tanks have randomly assigned one of 4 food treatments - S(tarve), L(ow), M(edium) and H(igh). There are 3 reps of each treatment. I collect data on size of each

Dear R helpers exposure <- data.frame(id = c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20), ead = c(9483.686,50000,6843.4968,10509.37125,21297.8905,50000,706152.8354, 62670.5625, 687.801995,50641.4875,59227.125,43818.5778,52887.72534,601788.7937, 56813.14859,4012356.056,1419501.179,210853.4743,749961,6599.0862), pd =

Hello, guys! I'm a novice at programming, learning about the speex and its applications now. Specifically, my current goal is to encode microphone input on iOS device in real-time, saving result to a file frame-by-frame. So far, I've managed to: 1) compile speex static library (it works, at least for iPhone/iPad, but not on iOS simulator; this is fine for now); 2) encode pcm data from

Hello, guys! I'm a novice at programming, learning about the speex and its applications now. Specifically, my current goal is to encode microphone input on iOS device in real-time, saving result to a file frame-by-frame. So far, I've managed to: 1) compile speex static library (it works, at least for iPhone/iPad, but not on iOS simulator; this is fine for now); 2) encode pcm data from

Hello, guys! I'm a novice at programming, learning about the speex and its applications now. Specifically, my current goal is to encode microphone input on iOS device in real-time, saving result to a file frame-by-frame. So far, I've managed to: 1) compile speex static library (it works, at least for iPhone/iPad, but not on iOS simulator; this is fine for now); 2) encode pcm data from

Hello, guys! I'm a novice at programming, learning about the speex and its applications now. Specifically, my current goal is to encode microphone input on iOS device in real-time, saving result to a file frame-by-frame. So far, I've managed to: 1) compile speex static library (it works, at least for iPhone/iPad, but not on iOS simulator; this is fine for now); 2) encode pcm data from

I was experiencing a strange pattern of slowdowns when using sample.int(), where sampling from a one population would sometimes take 1000x longer than taking the same number of samples from a slightly larger population. For my application, this resulted in a runtime of several hours rather than a few seconds. Looking into it, I saw that sample.int() is hardcoded to switch algorithms when the

Dear R users, I am trying to simulate some multitrait-multimethod models using the packages sem and psych but whatever I do to deal with models which do not converge I always get stuck and get error messages such as these: "Error in summary.sem(M1) : coefficient covariances cannot be computed" "Error in solve.default(res$hessian) : System ist f?r den Rechner singul?r: reziproke

Dear colleague, I not sure this R code is correctly ? I would to show the number of Sample Size at Sample Size Axis that line draw from Power Axis (80%) from R code. How I show this and select the most appropriate of this power (.79955687 - 80983575). Thank for your help and answer. Best Regards, Nikom Thanomsieng, Email: nikom at kku.ac.th .... #Power analysis: Sample size for

Hallo! I found a question exactly as mine, but I did not found an answer. Therefore?I post this again - hopefully there will be an answer! Thanks in advance! karl From: Berta <ibanez> Date: Tue, 27 Feb 2007 18:58:48 +0100 Hi R-users, I want to calculate the sample size needed to carry out a 2-sample proprotion test. I have the hypotesized treatment probability of success (0.80), the

I generate random vector from Weibull distribution sampWB <-urweibull(sampleSize, shape=shape.true, scale=scale.true, lb=0, ub=Inf) how can I create subvector containing 30% of samplesize of sampWB which should be assigned as Censored data? The probability for each value in sampWB can be uniform to be included in the subvector.

Hi I'm conducing a meta-analysis using the meta package. Here's a bit of code that works fine - tmp <- metacont(samplesize.2, pctdropout.2, sddropout.2, samplesize.1, pctdropout.1, sddropout.1, data=Dataset, sm="WMD") I would now like to control for a couple of variables (continuous and categorical) that aren't in the equation. Is meta

sampleSize <- 20 shape.true <- 1.82 scale.true <- 987 sampWB <- rweibull(sampleSize, shape=shape.true, scale=scale.true) print(sampWB) censidx <- sample(1:length(sampWB), length(sampWB)*0.3) Censored.data <- sampWB[censidx] noncensidx <- defines the rest values of the vector which is not included at Censored.data? [[alternative HTML version deleted]]

Hi, I write below code for simulation for weibull- estimating parameters by weibullMLE function, Although I define metrix for the variables still I got this message: number of items to replace is not a multiple of replacement length Any suggestion > est=matrix (NA, 2,2) > se=matrix (NA, 2,2) > for ( p in 1:2) { + sampleSize <- 20 + shape.true <- 1.82 + scale.true <- 987 +