similar to: R-function available for noncentral hypergeometric distribution

Let A be a m by n matrix and b a length n vector. What is the fastest vectorized code for doing for(j in 1:n) A[, j] <- A[, j]/b[j] ? solution 1: t(t(A)/b) solution 2: B <- matrix( rep(b, m), byrow=T, nrow=m ) A/B anything else? I have a program that uses this kind of operation million of times and I appreciate your input. Thanks. Jason Liao ===== Jason G. Liao Department of

This is some kind of follow-up to my previous posts. I have further improved the speed of my program 6 times by eliminating all the apply(). It turns out that apply is slow, is slower than direct loop, it is an order slower than a matrix operation alternative. Here is one example. The first apply version runs 19 seconds, the second loop version runs 13 seconds, the third matrix version runs 1

The following runs in an eyeblink on my 700Mhz Thinkpad T-20 (256 MB RAM) with Windows NT: var(matrix(rnorm(4000000),ncol=4,nrow=1000000)) This also has the virtue of being quite readable. You could allow an arbitrary covariance matrix and mean vector and it increases the time slightly, but still only about 5 seconds. Regarding performance, having tons of RAM is crucial. My Windows NT and the

Dear R Users, There exists a non-central hypergeometric distribution function in the (MCMCpack) package, and a hypergeometric distribution function in the (stats) package. Is there a function for sampling from an extended hypergeometric distribution? Thanks, Narcyz This message is intended for the addressee named and may con...{{dropped}}

I have been reading, in various sources, that a poisson distribution is related to binomial, extending the idea to include numbers of events in a given period of time. In my case, the hypergeometric distribution seems more appropriate, but I need a temporal dimension to the distribution. I have weekly samples of two kinds of events: call them A and B. I have a count of A events. These change

Hi, I hope somebody can help me on how to use the hypergeometric function. I did read through the R documentation on hypergeometric but not really sure what it means. I would like to evaluate the hypergeometric function as follows: F((2*alpha+1)/2, (2*alpha+2)/2 , alpha+1/2, betasq/etasq). I'm not sure which function should be used- either phyper or qhyper or dhyper Where

Dear R Users, I employed the phyper() function to estimate the likelihood that the number of genes overlapping between 2 different lists of genes is due to chance. This appears to work appropriately. Now i want to try this with 3 lists of genes which phyper() does not appear to support. Some googling suggests i can utilize the Multivariate hypergeometric distribution to achieve this. eg.:

I'd like to fit the (1-displaced) negative hypergeometric distribution to data samples such as the following:- x <- c(370, 311, 299, 266, 265, 232, 197, 198, 170, 154, 133, 123, 120, 103, 80, 72, 69, 67, 67, 50, 36, 35, 26, 23, 15, 11, 9, 6, 5, 3, 3, 2, 2, 2) i.e., I want to estimate the parameter values of K and M (with my data, n would usually be the same as the length of the data

Is there any way to know how the "dmvt" function computes the hypergeometric function needed in the calculation for the density of multivariate t distribution? -- View this message in context: http://r.789695.n4.nabble.com/hypergeometric-function-in-mvtnorm-tp4483730p4483730.html Sent from the R help mailing list archive at Nabble.com.

Hello. Somebody knows how to compute generalized hypergeometric series in R? (see http://functions.wolfram.com/HypergeometricFunctions/HypergeometricPFQ/02/ to understand what I mean) Thanks in advance, Arnau.

Dear All, I am looking for an implementation in R of the Appell Hypergeometric function. Any suggestions will be more than appreciated! GP -- dr. Giovanni Parrinello External Lecturer Medical Statistics Unit Department of Biomedical Sciences Viale Europa, 11 - 25123 Brescia Italy Tel: +390303717528 Fax: +390303717488 email: parrinel at med.unibs.it

A cut and paste typo has crept in and is rendering all values returned for the hypergeometric distribution incorrect. The problem is in src/main/arithmetic.c in the function "math4". The lines PROTECT(sy = allocVector(REALSXP, n)); a = REAL(sa); b = REAL(sb); c = REAL(sc); d = REAL(sc); /* <-- change this line */ y = REAL(sy); should

Dear R team, I have a simple question. I tried this command: phyper(17,449,19551,181, FALSE) [1] 1.47295e-07 and then I tried this command: (fisher.test(matrix(c(17,449,181,19551),2,2), alternative='greater'))$p.value [1] 3.693347e-06 Shouldn't be identical the results of the two commands ? What is the difference ? Thx a lot -- View this message in context:

Hi, Actually I am facing a similar problem. I would like to fit both an ordinary (symmetric) and a non-central t distribution to my (one-dimensional) data (quite some values.. > 1 mio.). For the symmetric one, fitdistr or funInfoFun (using fitdistr) from the qAnalyst package should do the job, and for the non-central one.. am I right to use gamlss(x ~ 1, family=GT()) ? Anyway, I am a little

Dear list, I have performed several tests for the hypergeometric distribution using phyper() for some gene annotation categories as follows >phyper(26,830,31042,337, lower.tail=F) >phyper(16,387,31042,337, lower.tail=F) . . . I am only running some selected categories but I would like to correct this value for multiple testing since I have 3121 possible tests according to 3121

In both versions of R to which I currently have access (R-0.16.1 and R-0.61.1), "phyper" stops returning correct cumulative probabilities as the parameters of the hypergeometric distribution get large. For example, when N1=1345, N2=1055, and n=1330, phyper returns either 0 or 1, and nothing in between. Looking at phyper.c, it's clear what's happening. First a term (called

Hi, I'm an R newbie and I've got a question regarding a certain function in R. I need to calculate values of the hypergeometric 2f1 function (hyp2f1 in cephes math library, Hypergeometric2f1 in Mathematica) and I'm wondering if anyone has tried to implement it in R or S-Plus. If not, what would be the prefered way to do so? Should I rather try to use an external C module or implement

I'm going to use dhyper(x, m, n, k) to get a 95% coverage. Let me use an example to explain my problem: Suppose I have a urn containing 90 red and 10 black balls. Now I wanna remove 3 from the urn. By the following codes: m<-90;n<-10;k<-3; x<-0:3 dhyper(x,m,n,k) I can obtain the probability that 0,1,2,3 red balls will be removed. 0.000742115 0.025046382 0.247680891

Dear List: The square of the noncentral t-statistic with noncentrality parameter \delta is a noncentral F with noncentrality parameter \lambda=\delta^2. So, t^2_{\nu,\delta} = F_{1,\nu,\lambda=\delta^2}. Consequently, it should follow that t^2_{1-\alpha/2,\nu,\delta} = f_{1-alpha,1,\vu,\lambda=\delta^2}. However, this is not what is happening with the following code. The central

"help" We want to estimate the number of caribou in Jasper. We recently conducted an aerial survey and saw 70 uncollared caribou and 8 of 11 collared caribou. We want to estimate the number of caribou in this population with 95% confidence limits. Gary White uses the hypergeometric distribution and determines the population estimates using maximum likelihood and 95%CL as