similar to: inaccuracy in qbinom with partial argument matching

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

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

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:

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:

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.

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?

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

On Sun, 1 Jul 2001 mcdowella@mcdowella.demon.co.uk wrote: > Full_Name: Andrew Grant McDowell > Version: R 1.1.1 (but source in 1.3.0 looks fishy as well) > OS: Windows 2K Professional (Consumer) > Submission from: (NULL) (194.222.243.209) Please upgrade: we've found a number of Win2k bugs and worked around them since then, let alone teh bug fixes and improvements in R .... >

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

Hi, I'm having a problem using sample() within a function. Basically I get an error reading: Error in sample(v, 1, prob = h) : non-positive probability Can anyone advise me as to the possible origin of this error? Here is my code #Discretised Gillespie algorithm function (From SMfSB, D.J. Wilkinson) gillespied=function (N, T=100, dt=1, ...) { tt=0 n=T%/%dt x=N$M

This code worked fine for me, then did some cleaning up of formatting using ESS (Emacs) and now I get this error, no idea what is causing it, all the brackets/parentheses seem to be balanced. What have I done wrong? Thanks Jim p0.trial01 <- 0.25 TruOR01 <- 0.80 num.patients.01 <- 50 num.trials.01 <- 5 LOR01.het.in <- 0.00 num.sims <- 1 simLOR01 <-

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

Hi I would like to solve a system of nonlinear equations below using dfsane function   mn <- 142.36; vr <- 9335.69 ; sk <- 0.81;  kur <- 0.25 test_fn <- function(p) {    f <- rep(NA, length(p))     f[1] <- p[1]*(p [2]+p[3])- mn   f[2] <- - vr + 2*p[1]*p[2]*p[3]*(p[4]-1)+p[1]*(p[2]+p[3])^2   f[3] <- - sk + (p[1]*(p [2]+p[3])^3*(p[1]+1)*(p[1]+2)-6*p[1]*p[2]*p[3]*(p[2]+

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              

I am tangled with a syntax question. I want to calculate basic statistics for a large dataset provided in weights and values and I can't figure out an elegant way to expand the data. For example here are the counts: > counts n4 n3 n2 n1 p0 p1 p2 p3 p4 1 0 0 0 1 1 3 16 55 24 2 0 0 0 0 2 8 28 47 15 3 1 17 17 13 4 5 12 24 8 ... and the values: > values

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

Using a line width > 1 results in not only a thicker line but also some fuzz in the other direction, as shown in this example program. You will see that the thick vertical black lines extend below the gray scale horizontal lines. Does anyone know whether this is intended or is it a bug? The application is for displaying a correlation matrix (here just some random U(0,1)s). Thanks -Frank