search for: pbinom

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] 0.729...

Btw, all the pbinom() examples posted to S-news today return the proper result in R Martin >>>>> "JS" == James Stapleton <stapleton at stt.msu.edu> writes to S-news : JS> More interesting behavior of pbinom: >> pbinom(3,2,.8) JS> [1] 1 >> pbinom(30,2,...

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 relies on the normal asymptotics. So I would imagine the binom.test should be equal to one of the other two lines, but it is not. The same happ...

This came up due to a question from Anders Hald: Bernoulli calculated an approximation to the smallest n so that P(0.58 <= x/n <= 0.62) >= 1000/1001 What is the exact value? Now try n <- 6350:6500 Pr <- function(n)pbinom(0.62*n,n,0.6) - pbinom(0.58*n,n,0.6) + dbinom(0.58*n,n,0.6) plot(n,Pr(n),type="b") abline(h=1000/1001) min(n[Pr(n)>1000/1001]) Next, try Pr <- function(n)pbinom(0.62*n,n,0.6) - pbinom(0.58*n + 1e-7,n,0.6) + dbinom(0.58*n,n,0.6) plot(n,Pr(n),type="b") abline(...

...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) && pbinom(c, n, p2) <= beta Where p1 (AQL) and p2 (LTPD) are probabilities parameters (Consumer and Producer), the alpha and beta are conumer and producer risks, and finally, the 'n' represents the sample size and the 'c' an acceptance number or maximum number...

On Feb 10, 2005, at 7:38 PM, George W. Gilchrist wrote: > Today I was running a graduate level stats lab using R and we > encountered a > major problem while using the current build of the Cocoa GUI: > >> From the GUI: >> system.time(pbinom(80, 1e5, 806/1e6)) > [1] 14.37 4.94 30.29 0.00 0.00 >> > >> From the command line on the same machine: >> system.time(pbinom(80, 1e5, 806/1e6)) > [1] 0.02 0.00 0.02 0.00 0.00 >> > > I've tried the CRAN version and the latest build of the R-GUI and both...

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...

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: 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

...M] > Sent: Friday, February 14, 2003 1:29 PM > To: Stratowa,Dr,Christian FEX BIG-AT-V > Cc: r-help at stat.math.ethz.ch; David Smith > Subject: Re: [R] FW: [Fwd: Re: [S] Exact p-values] > > To understand the correct answer, you need to understand the following: > > > pbinom(1, 2, .5) > [1] 0.75 > > This is the binomial cumulative distribution function. > *** pbinom(0, 2, .5) = 0.25 > *** pbinom(1, 2, .5) = 0.75 = 0.25 + 0.5 > *** pbinom(2, 2, .5) = 1 > > However, pbinom(1e15, 2e15, .5) is a computational challenge. Standard > numerical a...

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 inst...

The real problem is that pbeta can take forever. That's bug #7153 and a fix is within reach. Morten

Dear all Just for fun, I have just downloaded the paper mentioned below and checked it with R-1.6.1. Everything is ok with exception of Table 2b, where I get always 1 instead of 0.5: > pbinom(1e15,2e15,0.5) [1] 1 Which value should be correct? Best regards Christian Stratowa ============================================== Christian Stratowa, PhD Boehringer Ingelheim Austria Dept NCE Lead Discovery - Bioinformatics Dr. Boehringergasse 5-11 A-1121 Vienna, Austria Tel.: ++43-1-80105-2470...

...est should work (both quite possible)... > > >Thanks, >JT.. > > > >> #### 1000 random samples from binomial dist with mean =.25, n=100... >> o<-rbinom (1000, 100, .25) >> mean (o); >[1] 25.178 >> var (o); >[1] 19.61193 >> ks.test (o, "pbinom", 100, .25); > > One-sample Kolmogorov-Smirnov test > >data: o >D = 0.0967, p-value = 1.487e-08 >alternative hypothesis: two.sided > > > >p-value is mighty small, leading me to reject the null hypothesis that >the sample has been drawn from the Bin(1...

...lt;- 1 + 1e-07 d <- dbinom(x, n, p) m <- n * p if (x == m) 1 else ## PVAL if x < m if (x < m) { i <- seq(from = ceiling(m), to = n) y <- sum(dbinom(i, n, p) <= d * relErr) ## here: pbinom(x,n,p) + pbinom(n-y,n,p,lower=FALSE) } ## PVAL if x > m: else { i <- seq(from = 0, to = floor(m)) y <- sum(dbinom(i, n, p) <= d * relErr) ## here: pbinom(y-1,n,p) + pbinom(x-1,n,p,lower=FALSE) } }...

...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) [1] 0.975 # i.e., upper 2.5% of distribution I would think I generally want a 95% CI on the observed 9 out of 20, not 8 out of 20 LB and 9 out of 20 UB. I am missing something or is this strictly a function of the beta approximatio...

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

...Thanks, > >JT.. > > > > > > > >> #### 1000 random samples from binomial dist with mean =.25, n=100... > >> o<-rbinom (1000, 100, .25) > >> mean (o); > >[1] 25.178 > >> var (o); > >[1] 19.61193 > >> ks.test (o, "pbinom", 100, .25); > > > > One-sample Kolmogorov-Smirnov test > > > >data: o > >D = 0.0967, p-value = 1.487e-08 > >alternative hypothesis: two.sided > > > > > > > >p-value is mighty small, leading me to reject the null hypothesis th...

...) && is.finite (conf.level) && (conf.level > 0) && (conf.level < 1))) stop("conf.level must be a single number between 0 and 1") DNAME <- paste(deparse(substitute(x)), "and", deparse(substitute(n))) PVAL <- switch(alternative, less = pbinom(x, n, p), greater = 1 - pbinom(x - 1, n, p), { pvec <- pbinom(0:n, n, p) if(x/n < p) { pb <- pbinom(x, n, p) p2 <- max((1 - pvec) [pb - (1 - pvec) >= - eps * pb], 0) min(1, pb + p2) } else { pb <- (1 - pbinom(x - 1, n, p)) p2 <- max(pvec[pb...

I think the function you need is 'help.search'; try: help.search("binomial") and look for something obvious in the 'stats' package. A good deal quicker and easier than posting to an internet forum! Cheers, Mike. cathelf wrote: > > Dear all, > > I am trying a find the value "p" in binomial. > > X ~ Bin(n,p) > > I want to find the