similar to: binom.test() query

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

I believe the binom.test procedure is producing one tailed p values rather than the two tailed value implied by the alternative hypothesis language. A textbook and SAS both show 2*9.94e-07 = 1.988e-06 as the two tailed value. As does the R summation syntax from R below. It looks to me like the alternative hypothesis language should be revised to something like " ... greater than or equal

Hello all, I am trying to understand the different results I am getting from the following 3 commands: chisq.test(c(62,50), p = c(0.512,1-0.512), correct = F) # p-value = 0.3788 binom.test(x=62,n=112, p= 0.512) # p-value = 0.3961 2*(1-pbinom(62,112, .512)) # p-value = 0.329 Well, the binom.test was supposed to be "exact" and give the same results as the pbinom, while the chisq.test

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

R-experts: A quick question, please. >From a lab exp, I got 12 positives out of 50. To get 90% CI for this , I think binom.test might be the one to be used. Is there a better way or function to calculate this? > binom.test(x=12, n=50, p=12/50, conf.level = 0.90) Exact binomial test data: 12 and 50 number of successes = 12, number of trials = 50, p-value = 1 alternative

I am trying to find a definition for the two-tailed exact binomial test but have been unsuccessful. Can you help? --------------------------------- [[alternative HTML version deleted]]

running R 1.4.1 on MAC and 1.2.2 on Linux When I use run binom.test with small N the results are a little perplexing to me >binom.test(9,20,p=0.5) gives the below plus other stuff 95 percent confidence interval: 0.2305779 0.6847219 Now: >pbiom(9,20,0.6847219) [1] 0.02499998 # i.e., lower 2.5% of distribution >pbinom(9,20,0.2305779) [1] 0.9923132 >pbinom(8,20,0.2305779)

Hi, With the following Sweave minimal file: ---<--------------------cut here---------------start------------------->--- \documentclass{article} \usepackage{Sweave} \begin{document} <<binom-sim>>= thetas <- seq(0, 1, by=0.001) prior <- rep(1, length(thetas)) / length(thetas) lik <- dbinom(1, 1, thetas) lik.p <- prior * lik post <- lik.p / sum(lik.p)

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)

In principle a good idea, but I'm not sure the whereabouts of Catherine Loader are known at this point. Last peeps from her on the net seem to be about a decade old. .pd > On 18 May 2020, at 10:31 , Abby Spurdle <spurdle.a at gmail.com> wrote: > > This has come up before. > > Here's the last time: > https://stat.ethz.ch/pipermail/r-devel/2019-March/077478.html

Full_Name: Petr Savicky Version: 2.4.0 OS: Fedora Core release 2 Submission from: (NULL) (62.24.91.47) the error is > binom.test(0.56*10000,10000) Error in binom.test(0.56 * 10000, 10000) : 'x' must be nonnegative and integer while > binom.test(5600,10000) yields correct result. The same error occurrs for > binom.test(0.57*10000,10000)

Hello everybody. Does anyone else find the last test in the following sequence odd? Can anyone else reproduce it or is it just me? > binom.test(100,200,0.13)$p.value [1] 2.357325e-36 > binom.test(100,200,0.013)$p.value [1] 6.146546e-131 > binom.test(100,200,0.0013)$p.value [1] 1.973702e-230 > binom.test(100,200,0.00013)$p.value [1] 0.9743334 (R 1.5.1, Linux RedHat 7.1) --

R. 1.1.0 The example below is self explanatory. ## 1 ## # works fine > binom.test((50*.64),50,.5,alt='g') ... Exact binomial test ... ## 2 ## # WHAT ! ? > binom.test((50*.65),50,.5,alt='g') Error in binom.test((50 * 0.65), 50, 0.5, alt = "g") : x must be an

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

No, since I'd like to test null: p <= p0 alternative: p > p0. and my understanding is that binom.test tests null: p = p0 (can only be a "simple" null hypothesis according to help(binom.test)) alternative: p > p0 (or p < p0 or p != p0). Thanks, Mirko. > -----Urspr?ngliche Nachricht----- > Von: Douglas Bates [mailto:bates at stat.wisc.edu] >

FWIW the link from ?dbinom to the Loader paper on Binomials is broken but the paper seems to be available here: https://octave.1599824.n4.nabble.com/attachment/3829107/0/loader2000Fast.pdf Roger Koenker r.koenker at ucl.ac.uk<mailto:r.koenker at ucl.ac.uk> Honorary Professor of Economics Department of Economics, UCL Emeritus Professor of Economics and Statistics, UIUC [[alternative

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(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

R 0630 for windows > library(ctest) > binom.test(7,10,p=0.3, alternative="two.sided") returns a p-value of =< 2.2e-016 and a warning In Splus 3.4 > binom.test(7,10,p=0.3, alternative="two.sided") returns a p-value of 0.0106 I think it is the max(v[v<=(1+eps)*PVAL]) causing the problem... max() of an empty vector....... Mai Z

On Mon, Mar 12, 2018 at 2:18 PM, Martin Maechler <maechler at stat.math.ethz.ch> wrote: > [...] > Is that so? Not according to my reading of the 'Writing R > Extensions' manual, nor according to what I have been doing in > all of my packages for ca. 2 years: > > The rule I have in my mind is > > 1) NAMESPACE Import(s|From) \ >