search for: hypergeometrically

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}}

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

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

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.

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.:

For those who are interested, I have made available a R function for noncentral hypergeometric distribution at http://www.geocities.com/jg_liao/software/Hypergeometric/hypergeometric_in_R.txt The paper that describes the algorithm will appear in The American Statistician. The function does not run on S-plus as the R's scoping rule is used. Here is how the function can be used: > n1

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

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 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:

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

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

"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

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

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

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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

Dear All I have a question about the hypergeomteric distribution. Example 1: I have a universe of 6187 objects, and 164 have a particular attribute, therefore 6187-164 do not have that attribute. I sample 249 of those objects, and find that 19 have that attribute. I get a p-value here (looking at just over-representation): phyper(19, 164, 6187-164, 249, lower.tail=FALSE) [1] 7.816235e-06

R Help on 'chisq.test' states that "if 'simulate.p.value' is 'TRUE', the p-value is computed by Monte Carlo simulation with 'B' replicates. In the contingency table case this is done by random sampling from the set of all contingency tables with given marginals, and works only if the marginals are positive... In the

Hello! I use R-version 1.0.0 To get the 0.95 quantile of the hypergeometric distribution with the parameters m=45000,n=5000 and k=600 I use the R-command > qhyper(0.95,45000,5000,600). The value obtained is 600. However, the true value is 552. The latter can be obtained for example by calling the corresponding distribution function with the R commands > x<-540:580 >