similar to: qbinom returns NaN

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,

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

n_10;p_0.5;jjx_0:n;qbinom(pbinom(jjx,n,p),n,p) # This one works as expected n_100;p_0.5;jjx_0:n;qbinom(pbinom(jjx,n,p),n,p) # This one causes severe problems I cannot interrupt using ESC and I finally have to resort to the Windows Task manager to kill the R session. A friend of mine told me that he faced similar problems under Unix. --please do not edit the information below-- Version:

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:

Full_Name: Chanseok Park Version: R 2.2.1 OS: RedHat EL4 Submission from: (NULL) (130.127.112.89) pbinom(any negative value, size, prob) should be zero. But I got the following results. I mean, if a negative value is close to zero, then pbinom() calculate pbinom(0, size, prob). dbinom() also behaves similarly. > pbinom( -2.220446e-22, 3,.1) [1] 0.729 > pbinom( -2.220446e-8, 3,.1)

(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

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

Hello all, A friend just showed me how ks.test fails to work with pbinom for small "size". Example: x<-rbinom(10000,10,0.5) x2<-rbinom(10000,10,0.5) ks.test(x,pbinom,10,0.5) ks.test(x,pbinom,size = 10, prob= 0.5) ks.test(x,x2) The tests gives significant p values, while the x did come from binom with size = 10 prob = 0.5. What test should I use instead ? Thanks, Tal

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.

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

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

Dear R users, I?m trying to optimize simultaneously two binomials inequalities (used in acceptance sampling) which are nonlinear solution, so there is no simple direct solution. Please, let me explain shortly the the problem and the question as following. The objective is to obtain the smallest value of 'n' (sample size) satisfying both inequalities: (1-alpha) <= pbinom(c, n, p1)

Full_Name: Uffe H?gsbro Thygesen Version: 2.2.0 OS: linux Submission from: (NULL) (130.226.135.250) Hello all. pbinom(q=0,size=0,prob=0.5) returns the value NaN. I had expected the result 1. In fact any value for q seems to give an NaN. Note that dbinom(x=0,size=0,prob=0.5) returns the value 1. Cheers, Uffe

Cordial saludo Tengo una duda sobre como poner el valor de un argumento de una funcion en el titulo de una grafica, es decir, mi funcion es: CO<-function(n,c) { Prob<-sapply(seq(0,0.15,0.01),pbinom,size=n,q=c) coor<-cbind(seq(0,0.15,0.01),Prob) plot(seq(0,0.15,0.01),Prob,type="b",xlab="Fracción defectuosa", ylab="Probabilidad",main="Probabilidad de

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

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              

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

Hi, I would have thought that these two constructions would produce the same result but they do not. Resp <- rbinom(10, 1, 0.5) Stim <- rep(0:1, 5) mm <- model.matrix(~ Stim) Xb <- mm %*% c(0, 1) ifelse(Resp, log(pnorm(Xb)), log(1 - pnorm(Xb))) pnorm(as.vector(Xb), lower.tail = Resp, log.p = TRUE) > ifelse(Resp, log(pnorm(Xb)), log(1 - pnorm(Xb))) [1] -0.6931472 -1.8410216