similar to: Weibull simulation- number of items to replace is not a multiple of replacement length

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.

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' 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 =

Hi, I'm 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 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

Dear Knowledgeable R Community Members, Please excuse my ignorance, I apologize in advance if this is an easy question, but I am a bit stumped and could use a little guidance. I have a finite mixture modeling problem -- for example, a 2-component Weibull mixture -- where the components have a large overlap, and I am trying to adapt the "mclust" package which concern to normal

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 =

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

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

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

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

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

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

Dear R-users, Using Maximum-likelihood Fitting (fitdistr function) I've got the next error: > fitdistr(datos,"weibull",lower=0) Error in optim(x = c(1.4625e-06, 0.257854, 0.0001217545, 0.11421005, 0.028721576, : L-BFGS-B *needs finite values of 'fn' * where "datos" is a vector of length=1000 between 1.4625e-06 and 0.8867114 I add the lower argument in

Hi, I have a data set which is assumed to follow weibull distr'. How can I find of cdf for this data. For example, for normal data I used (package - lmomco) >cdfnor(15,parnor(lmom.ub(c(df$V1)))) Also, lmomco package does not have functions for finding cdf for some of the distributions like lognormal. Is there any other package, which can handle these distributions?