similar to: Bug in qbinom? (PR#511)

Full_Name: Wolfgang Resch Version: R 2.8.1 GUI 1.27 OS: OS X 10.4.11 Submission from: (NULL) (137.187.89.14) Strange behavior of qbinom: > qbinom(0.01, 5016279, 1e-07) [1] 0 > qbinom(0.01, 5016279, 2e-07) [1] 16 > qbinom(0.01, 5016279, 3e-07) [1] 16 > qbinom(0.01, 5016279, 4e-07) [1] 16 > qbinom(0.01, 5016279, 5e-07) [1] 0

Hi, All: For most but not all cases, qbinom is the inverse of pbinom. Consider the following example, which generates an exception: > (pb01 <- pbinom(0:1, 1, .5, log=T, lower.tail=FALSE)) [1] -0.6931472 -Inf Since "lower.tail=FALSE", Pr{X>1} = 0 in this context, and log(0) = -Inf, consistent with the documentation. However, the inverse of this does NOT

Hi, I found the following strange effect with qbinom & partial argument matching p0 <- pbinom(0, size = 3, prob = 0.25) qbinom(p0, size = 3, prob = 0.25) ## 0 o.k. qbinom(p0-0.05, size = 3, prob = 0.25) ## 0 o.k. ## positional matching: qbinom(p0, 3, 0.25) ## 0 o.k. ## partial argument matching: qbinom(p0 , s = 3, p = 0.25) ## 1 ??? qbinom(p0-0.05,

a=c(0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9) b=c(0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, 0.1) cor(a,b)= -1 a'=qbinom(a, 1, 0.5) b'=qbinom(b, 1, 0.5) why cor(a',b') becomes -0.5 ? -- View this message in context: http://r.789695.n4.nabble.com/qbinom-tp4651460.html Sent from the R help mailing list archive at Nabble.com.

Full_Name: Jonathan Swinton Version: 1.8.0 OS: Windows 2000 Submission from: (NULL) (193.132.159.34) Calling qbinom with a sample probability of 1 returns NaN > qbinom(p=0.95,size=10,prob=1) [1] NaN I believe that this is wrong and that qbinom(p,size,prob=1) should always be size for 0<p<=1. The documentation says that The quantile is defined as the smallest value x such that F(x)

Full_Name: Jon McAuliffe Version: 1.9.0 OS: Mac OS X 10.3.4 Submission from: (NULL) (64.166.16.252) a call like qbinom(0.3, 10, prob = 0, lower.tail = FALSE) hangs R. prob = 0 does not look interesting, but it can be useful for completeness when qbinom is part of other general routines. please see PR#5900 (Accuracy-fixed). jon. --please do not edit the information below-- Version:

Dear friends, I'm probably wrong but is there anything better than bootstrap to get a confidence interval of the median from a population with unspecified distribution ? Best wishes Troels Ring, Aalborg, Denmark

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

Hi all, I am wondering whether there is a small bug in the binom.test function of the ctest library (I'm using R 1.6.0 on windows 2000, but Splus 2000 seems to have the same behaviour). Or perhaps I've misunderstood something. the command binom.test(11,100,p=0.1) and binom.test(9,100,p=0.1) give different p-values (see below). As 9 and 11 are equidistant from 10, the mean of the

(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

Hello! I'm having some trouble  trying to replicate in R a Stata function  invbinomial(n,k,p)        Domain n:     1 to 1e+17        Domain k:     0 to n - 1        Domain p:     0 to 1 (exclusive)        Range:        0 to 1        Description:  returns the inverse of the cumulative binomial; i.e., it                          returns the probability of success on one trial such              

rbinom (in R-1.4.1) silently rounds its "size" argument. The C code contains n = floor(nin + 0.5); I would argue that this should this either be documented or changed (to return NA). (The behavior is inconsistent with dbinom). I sent this in to the devel list a couple of weeks ago to provoke discussion; no disagreement (or agreement) so I'm submitting it as a bug.

Dear All Where can I lookup good methods to compute p from q=bin(m,n)p^n*(1-p)^(m-n) such that q<=alfa, alfa small. Are there such libs, code and source in R? Best Regards -- Jan Burse SIAM, EAWAG Scheuchzerstr. 67 ?berlandstr. 133 8006 Z?rich 8600 D?bendorf tel: +41-1-364 17 66 tel: +41-1-823 55 34

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

I'm trying to compute sample size requirements for a binomial exact test. we want to show that the proportion is at least 90% assuming that it is 95%, with 80% power so any asymptotic approximations are out of the questions. I was planning on using binom.test to perform the simple test against a prespecified value, but cannot find any functions for computing sample size. do any exist?

On 08/04/2023 5:53 p.m., Martin Maechler wrote: >>>>>> Christophe Dutang >>>>>> on Sat, 8 Apr 2023 14:21:53 +0200 writes: > > > Dear all, > > > Using rmultinom() in a stochastic model, I found this function returns an error message 'NA in probability' for an infinite probability. > > > Maybe, a more

I'm having sporadic problems with glm on my alpha workstation running Compaq Tru64 UNIX V5.0 (I can't replicate the problem on my Linux PC). I have the same problem whether I use a version of R built with the native C-compiler or a version compiled with gcc. In both cases I've built with g77. I want to do some simulations with a call to glm in each rep. A simplified version would be

Dear R-helpers: (this is part of a bigger program) the following fails as a function, but runs OK if we comment out the fnfn_ function() line. Any hint would be appreciated. -Yudi- R : Copyright 1998, The R Development Core Team Version 0.63.0 Beta (Nov 13, 1998) -- on WIndows3.11 fnfn _ function (m=10,n=10,spar=2) { fn _ function(u,v){ uc_ u-floor(m/2)-1 vc_ v-floor(n/2)-1

Hi R-fellows, I am trying to simulate a multivariate correlated sample via the Gaussian copula method. One variable is a binary variable, that should be autocorrelated. The autocorrelation should be rho = 0.2. Furthermore, the overall probability to get either outcome of the binary variable should be 0.5. Below you can see the R code (I use for simplicity a diagonal matrix in rmvnorm even if it