similar to: Arrays and functions

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, 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 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 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

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

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 +

Please forgive me, I feel exceptionally like a newbie. Although I've read screeds of documentation, I just can't see how this is done. I have a data frame that contains a number of pass/fails for certain variable sizes. From that, I would like to form another data frame that contains the proportions of pass/fails per variable. So, for example: df <- data.frame( Var=c(3,3,3,4,4),

Hi, Don't know if it belongs to r-devel or r-help, but since I am planning to alter some of R's internal code I am sending it here. The existing implementation of the sample() function, when the optional 'prob' argument is given, is quite inefficient. The complexity is O(sampleSize * universeSize), see ProbSampleReplace() and ProbSampleNoReplace() in random.c. This makes the

Hi all: I have a question on sample size calculation of 2 groups of data. If 2 groups of data are all normal distribution, then I can use the function "n.indep.t.test.eq" from samplesize package.But if 2 groups of data are all skewed distribution, but not normal distribution,how can I calculate the sample size then? I've tried many transformation (e.g. log arcsin…) in order to

hello all, I would like to introduce a summary table into the pdf along with the plots (in order to archive my data into single files automatically). Similarly, It would be great to have the result of the statistical analysis (for instance anova) in the same file. Is there a way to do that? example: pdf("example.pdf") layout (matrix(1:2,1,2)) plot (groups, scores) Result <-

Thank you for the reference to Knuth. Indeed in vol. 2 he has a > -----Original Message----- > From: Tony Plate [mailto:tplate@blackmesacapital.com] > Sent: Friday, September 24, 2004 8:05 AM > To: Vadim Ogranovich > Subject: Re: [Rd] algorithm reference for sample() > > Have you tried looking in Knuth's books on computer > algorithms? (They are classics for good

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

On 05/10/2018, 09:45, "R-help on behalf of hmh" <r-help-bounces at r-project.org on behalf of hugomh at gmx.fr> wrote: Hi, Thanks William for this fast answer, and sorry for sending the 1st mail to r-help instead to r-devel. I noticed that bug while I was simulating many small random walks using c(0,cumsum(rnorm(10))). Then the negative

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