similar to: number of required trials

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

Thanks Ben for verifying the issue. It is always reassuring to hear when others can reproduce the problem. I wrote a small patch that fixes the issue (https://github.com/r-devel/r-svn/pull/11): diff --git a/src/nmath/qnbinom.c b/src/nmath/qnbinom.c index b313ce56b2..d2e8d98759 100644 --- a/src/nmath/qnbinom.c +++ b/src/nmath/qnbinom.c @@ -104,6 +104,7 @@ double qnbinom(double p, double size,

Hi Martin, thanks for verifying. I agree that the Cornish-Fisher seems to struggle with the small size parameters, but I also don't have a good idea how to replace it. But I think fixing do_search() is possible: I think the problem is that when searching to the left y is decremented only if `pnbinom(y - incr, n, pr, /*l._t.*/TRUE, /*log_p*/FALSE)) < p` is FALSE. I think the solution is

>>>>> Constantin Ahlmann-Eltze via R-devel >>>>> on Mon, 10 Aug 2020 10:05:36 +0200 writes: > Thanks Ben for verifying the issue. It is always reassuring to hear > when others can reproduce the problem. > I wrote a small patch that fixes the issue > (https://github.com/r-devel/r-svn/pull/11): > diff --git

Hi all, I recently noticed that `qnbinom()` can take a long time to calculate a result if the `size` argument is very small. For example qnbinom(0.5, mu = 3, size = 1e-10) takes ~30 seconds on my computer. I used gdb to step through the qnbinom.c implementation and noticed that in line 106 (https://github.com/wch/r-source/blob/f8d4d7d48051860cc695b99db9be9cf439aee743/src/nmath/qnbinom.c#L106)

(1) ...need to speed up a monte-carlo sampling...any suggestions about how I can get R to use all 8 cores of a mac pro would be most useful and very appreciated... (2) spent the last few hours trying to get pnmath to compile under os- x 10.5.4... using gcc version 4.2.1 (Apple Inc. build 5553) as downloaded from CRAN, xcode 3.0... ...xcode 3.1 installed over top of above after

This came up on r-help but indicates a bug. dnbinom(x,n,p) calls dbinom_raw(n-1,...) which returns 0 for n<1. -thomas ---------- Forwarded message ---------- Date: Thu, 08 Feb 2001 17:10:23 +0000 From: Yudi Pawitan <yudi@stat.ucc.ie> To: Mark Myatt <mark@myatt.demon.co.uk> Cc: R-Help <r-help@stat.math.ethz.ch> Subject: Re: [R] Goodness of fit to Poisson / NegBinomial

?? I can reproduce this on R Under development (unstable) (2020-07-24 r78910) Platform: x86_64-pc-linux-gnu (64-bit) Running under: Pop!_OS 18.04 LTS ? In my opinion this is worth reporting, but discussing it here first was a good idea.? Many more people read this list than watch the bug tracker, so it will get more attention here; once the excitement has died down here (which might be

All, I have some data on parasites on apple leaves and want to do a goodness of fit test to a Poisson distribution. This seems to do it: mites <- c(rep(0,70), rep(1,38), rep(2,17), rep(3,10), rep(4,9), rep(5,3), rep(6,2), rep(7,1)) tab <- table(mites) NSU <- length(mites) N <-

On a recent FreeBSD 8.0-CURRENT (i386) building R (any version) breaks with the following messages: ---------------------------------------------------------------------- [...snip...] gcc -std=gnu99 -I. -I../../src/include -I../../src/include -I/usr/local/include -DHAVE_CONFIG_H -g -O2 -c wilcox.c -o wilcox.o gcc -std=gnu99 -I. -I../../src/include -I../../src/include -I/usr/local/include

Hi! I have just downloaded the R-0.60.1 sources and have problems compiling R on a Sun Ultra 1 running Solaris 2.6 and gcc 2.7.2.1. I have not been able to find to find any compiling hints in the documentation or the FAQ. After ./configure I use make and get the output below. Any hints are welcome. I am not on the list, so please answer me directly too. Best regards Jens --- Jens Lund

I'm having some difficulty with graphing outputs of a GLM model I've been working. I have count data for both my predictor (only 1) and response variables, and I have pseudoreplication which I've modeled as a random effect. The odTest() from pscl:: indicated that the negative binomial distribution fit better than Poisson, and I then proceeded by estimating theta from glm.nb. My

Dear list, I ran into a strange behaviour of the pnbinom function - or maybe I just made a stupid mistake. First thing is that pnbinom seems to be very slow. The other - more interesting one - is that I get two different curves when I plot the estimated density and the density given by pnbinom. Shouldn't it be the same? This is only the case, I think, if I use the parameter size = 1. I

Dear R users, I was wondering from where I could get the C source code to compute pnbinom() and qnorm() ? (I would use R in batch mode but I find the startup time prohibitive, unless there is a way to speed it up) I searched the Web and it clearly is part of the R distribution, I just don't know how to extract them. Thanking you ! Markus Loecher Princeton, NJ [[alternative HTML version

Hi again ! Thanks for the info on updating the config.site file which I have done. I have also added -lm in the Makeconf manually because this is needed explicitly for DEC cc. However, there are still a few problems when linking some of the files as you can see from the enclosed log. Ciao, Andreas ------------------------------------------------------- R-0.63.3>make make[1]: Entering

Try changing your method to "ML" and try again. I tried the run the first example from the documentation and it failed with the same error. Changing the estimation method to ML worked. @List: Can anyone else verify the error I got? I literally ran the following two lines interactively from the example for goodfit: dummy <- rnbinom(200, size = 1.5, prob = 0.8) gf <- goodfit(dummy,

I used both BMDP and SAS in my earlier years, side by side. At that time the BMDP statistical methods were much more mature and comprehensive: we treated them as the standard when the two packages disagreed. (It was a BMDP manual that clearly explained to me what the hypothesis of "Yate's weighted mean test" is, something SAS decided to call "type III" and eternally

Dear All, I am looking an R version of the "Computer program for sample size and power calculations in the design of multi-arm and factorial clinical trials with survival endpoints". Best regards, Giovanni Parrinello P.S.: in the meantime I am preparing a summary for my preceeding question about time-varying covariates in the Cox model and I thank Frank Harrell, Chuck Cleland,

Hi there, I want to find the adjusted confidence intervals in group sequential trials in a simulation setting. GroupSeq provides me with what I am looking for in an interactive setting, but I am not sure how to make it work in a simulation setting so that it produces a series of adjusted confidence intervals for a series of Z-statistics that I provide it without me having to enter each