similar to: .Internal for functions in distn.R

There is a problem with `rpois'. It does seem to take care about the order of the arguments. This is an example: > rpois(n=1,lambda=2) [1] 3 > rpois(lambda=2,n=1) [1] 2 0 It obviously uses the first argument as the number of samples to be drawn, which is wrong. I used Version 0.49 Beta (April 23, 1997). Fredrik

There is a problem with `rpois'. It does seem to take care about the order of the arguments. This is an example: > rpois(n=1,lambda=2) [1] 3 > rpois(lambda=2,n=1) [1] 2 0 It obviously uses the first argument as the number of samples to be drawn, which is wrong. I used Version 0.49 Beta (April 23, 1997). Fredrik

1. lbeta and beta do not work properly: lbeta returns its first argument and beta gives the lbeta result. In names.c lines 245-6, the codes for these should be 2 and 3 instead of 1 and 2 2. crtl-C does not work (except the first time) on Red Hat elf Linux (which has many many other problems as well) nor on the previous version of Linux for Amiga. It worked on Slackware aout Linux and now works

1. lbeta and beta do not work properly: lbeta returns its first argument and beta gives the lbeta result. In names.c lines 245-6, the codes for these should be 2 and 3 instead of 1 and 2 2. crtl-C does not work (except the first time) on Red Hat elf Linux (which has many many other problems as well) nor on the previous version of Linux for Amiga. It worked on Slackware aout Linux and now works

On Sun, 27 Aug 2023 19:54:23 +0100 John Logsdon <j.logsdon at quantex-research.com> wrote: > Not so although it did lower the gc() time to 95.84%. > > This was on a 16 core Threadripper 1950X box so I was intending to > use library parallel but I tried it on my lowly windows box that is > years old and got it down to 88.07%. Does the Windows box have the same version of R

Folks I have come across an issue with gc() hogging the processor according to Rprof. Platform is Ubuntu 20.04 all up to date R version 4.3.1 libraries: survival, MASS, gtools and openxlsx. With default gc.auto options, the profiler notes the garbage collector as self.pct 99.39%. So I have tried switching it off using options(gc.auto=Inf) in the R session before running my program using

Hi, I believe I have significantly improved [dpq]wilcox functions by implementing Harding's algorithm: Harding, E.F. (1984): An Efficient, Minimal-storage Procedure for Calculating the Mann-Whitney U, Generalized U and Similar Distributions, App. Statist., 33, 1-6 Results on my computer show (against R-2.9.1): > system.time( dwilcox( 800, 800, 80) ) user system elapsed 0.240

Dear all, I am trying to simulate from truncated Pareto distribution. I know there is a package called PtProcess for Pareto distribution...but it is not for truncated one. Can anyone please help me with this? Thanks in advance. Cassie [[alternative HTML version deleted]]

I have dowloaded the Source Code of R,and I want to know the process of chi-sqared test,but how can I found it? [[alternative HTML version deleted]]

Hi,I am currently doing a project in which we are to investigate the size and power of three different one sample tests over three different distributions using a number of different sample sizes and values for mu1. I have written a function and was trying to get my answer for each test into the right position in an array so the output is the power of each combination of test, distribution, sample

Hi R-devels, I noticed that for the scheduled R 2.3.0, there is still no function df() for non-centrality != 0. Easter is quickly approaching, so as my little gift, I would like to offer you some code to fill this gap: After excluding some "unusual" cases, it amounts to differentiating the corresponding function pnf() --- which in turn leads to the function dnbeta() already available

Hi, I have a right-censored (positive) random variable (e.g. failure times subject to right censoring) that is observed for N subjects: Y_i, I = 1, 2, ..., N. Note that Y_i = min(T_i, C_i), where T_i is the true failure time and C_i is the censored time. Let us assume that C_i is independent of T_i. Now, I would like to generate another random variable U_i, I = 1, 2, ..., N, which is

Hi, I'm trying to use ad.test or ad2.test to test whether a given data set is exponential. I see that one of the function inputs is "distn", but I try "exponential" and 5 other variants, but I still get the error message: ad.test(test2, distn="exponential", fit=list(estimate = 0.167685), H=NA, sim=100) Error in ad.test(test2, distn = "exponential",

Hi, I was told to send this to the -devel list instead of posting to bugzilla. When round our signif are called with a single named argument, R does not check the name and runs the function with that named argument directly as the first argument, using 0.0 or 6.0 (6 in the case of signif) for the second argument. Not checking the argument name is at odds with how all other primitive functions

Hi, I've written some C code for density evaluation of the non-central t distribution. It works with the R-1.7.1 source code if placed in the src/nmath directory and after appropriate changes are made to Makefiles, to the dt function in src/library/base/R/distn.R etc. I haven't read a lot of R source code so it may need some R-ification, but I've tried to use the dt.c file as a

Hi, there was a change concerning logical operations about a year ago: https://github.com/wch/r-source/commit/9e19d3e3dd5f657b5cfefe562bdd7ede2e2b8786 It's related to a discussion on this list: https://hypatia.math.ethz.ch/pipermail/r-devel/2016-September/073068.html <https://hypatia.math.ethz.ch/pipermail/r-devel/2016-September/073068.html> A change in logic.c:134 influences the

Dear R users: I was trying to fit a HMM with mixture of Gaussian into the dataset, and I tried to implement it by R2Winbugs. But I got the following errer. * Error in FUN(X[[1L]], ...) : .C(..): 'type' must be "real" for this format* Does anybody know what's the problem? Does R2Winbugs accept some matrix as inits? I would really appreciate your help. Thank you very much.

While working on the printing code, my colleague Zbyn?k ?lajchrt noticed that complex matrixes are sometimes misaligned: > { matrix(1i,2,13) } [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [1,] 0+1i 0+1i 0+1i 0+1i 0+1i 0+1i 0+1i 0+1i 0+1i 0+1i 0+1i 0+1i 0+1i [2,] 0+1i 0+1i 0+1i 0+1i 0+1i 0+1i 0+1i 0+1i 0+1i 0+1i 0+1i 0+1i 0+1i (the values in the last four columns

Craig, Thanks for your follow-up note on using the asypow package. My problem was not only constructing the "constraints" vector but, for my particular situation (Poisson regression, two groups, sample sizes of (1081,3180), I get very different results using asypow package compared to my other (home grown) approaches. library(asypow) pois.mean<-c(0.0065,0.0003) info.pois <-

Hi all, I would like to estimate power and necessary sample size for a GLM with a response variable that has a poisson distribution. Do you have any suggestions for how I can do this in R? Thank you for your help. Sincerely, Craig -- Craig A. Faulhaber Department of Forest, Range, and Wildlife Sciences Utah State University 5230 Old Main Hill Logan, UT 84322 (435)797-3892