search for: lchoose

lgamma(x) and lfactorial(x) are defined to return ln|Gamma(x)| {= log(abs(gamma(x)))} or ln|Gamma(x+1)| respectively. Unfortunately, we haven't chosen the analogous definition for lchoose(). So, currently > lchoose(1/2, 1:10) [1] -0.6931472 -2.0794415 NaN -3.2425924 NaN -3.8869494 [7] NaN -4.3357508 NaN -4.6805913 Warning message: In lchoose(n, k) : NaNs produced > which (the NaN's) is not particularly useful. (I have use case...

Hello I have a time-comsuming program which need to simplify, I have tested the annotated program as follow: > #define function which will be call > calsta <- function(c, n=100000) + { + i <- seq(from=0, length=c) + logx <- lchoose(NT-n, CT-i) + lchoose(n, i) + logmax <- max(logx) + logmax + log(sum(exp(logx - logmax))) + } > CT=6000 #assignment to CT > NT=29535210 #assignment to NT > > vec<-c(2331,524,918,218,1100,547,289,1167,450,1723) > vec [1] 2331 524 918 218 1100 547 289 1167 450 172...

...9;t really have much to do with optim, so I changed >the subject line. > >It's difficult to see what you're trying to accomplish without a complete >example. Could you post one? Also, for loops are necessarily bad. > >One thing to note is that you're better off using lchoose in the above >code. I.e. > >log.s <- lchoose(j, i) + lchoose(k - j, l - i) - lchoose(k, l) >s[l] <- exp(log.s) > >--sundar > > I have a matrix of 200 by 2, namely z, the columns are i and j. K is the maximum of j. x0 is a k dimension vector. ss<-rep(0,200) for (...

...wrote a small function to sum its probabilities, modeled after phyper() and taking the arguments in the same order (the names have changed to suit the archaeological situation): > seber <- function(p,l,n,r) > { > y <- 0 > for (x in 0:p) > y <- y + exp(lchoose(l,x) + lchoose(n-l,r-x) - lchoose(n,r)) > y > } When used in the larger routine, this yields results that very closely approximate the results in Fieller and Turner's table 1. I initially thought I could use the function phyper() for this because, as I interpret the help files...

Hello I want to calculate natural logarithm of sum of combinations as follow: (R code) { com_sum=choose(2000000,482)*choose(1000000,118)+choose(2000000,483)*choose(1000000,117)+...+choose(2000000,i)*choose(1000000,600-i)+...+choose(2000000,600)*choose(1000000,0) #calculate the sum result=log(com_sum) #calculate the log of the sum } But

...r(1,10.5,90,10) > > # OK > qhyper(0.71,10,90,10) > qhyper(0.71,10.5,90,10) > > # OK > rhyper(1,10,90,10) > rhyper(1,10.5,90,10) > > > > # this "naive" version of dhyper() works > > dhyperx<-function(x,m,n,k,log=3DFALSE){ > lp<-lchoose(m, x) + lchoose(n, k-x) - lchoose( m+n, k) > if (log) {lp} else {exp(lp)} > } > > # OK > dhyperx(1,10,90,10) > dhyperx(1,10.5,90,10) > > > > Erik J=F8rgensen > Danish Institute of Agricultural Sciences > > > > --please do not edit the info...

...#39;t implement due to the precision problem i<-0:(c-1) vec<-choose(n,i)*choose(NT-n,CT-i) #get the vector which need summation result<-log(sum(vec)) #get the log of summation # thanks to Petr, we have a solution calsta <- function(c, n) { i <- seq(from=0, length=c) logx <- lchoose(NT-n, CT-i) + lchoose(n, i) logmax <- max(logx) logmax + log(sum(exp(logx - logmax))) } # now, new problem arise, in theory, the "result" of different (c,n) pair should most probably differ, so I can order them, but > calsta(918,100000)-calsta(718,100000) [1] 0 > calsta(718,...

Hi, I'm trying to calculate p-value to findout definitely expressed genes compare A to B situation. I got this data(this is a part of data) from whole organism , and each number means each expression values (that means, we could think 'a' gene is 13 in A situation, and it turns 30 in B situation) To findout probability, I'm going to use Audic - Claverie Method. ( The significance

...lose to integers (within 1e-7). In those cases, k is silently rounded to integer. As I read your suggestion, n would only be rounded to integer if k > n-k. I think both n and k should be rounded to integer in this near-integer situation, regardless of the value of k. > > I believe that lchoose(n, k) already does this. > > Duncan Murdoch > >> double r, k0 = k; >> k = R_forceint(k); >> ... >> if (fabs(k - k0) > 1e-7) >> MATHLIB_WARNING2(_("'k' (%.2f) must be integer, rounded to %.0f"), k0, k); >> &gt...

> On 14 Jan 2020, at 16:21 , Duncan Murdoch <murdoch.duncan at gmail.com> wrote: > > On 14/01/2020 10:07 a.m., peter dalgaard wrote: >> Yep, that looks wrong (probably want to continue discussion over on R-devel) >> I think the culprit is here (in src/nmath/choose.c) >> if (k < k_small_max) { >> int j; >> if(n-k < k

Dear R friends, I was wondering if there were factorial and modulus functions out there that I've somehow overlooked? -P. -- Peter L. Hurd, Ph.D. phurd at uts.cc.utexas.edu http://www.zo.utexas.edu/research/phurd fax 512.471-3878 Section of Integrative Biology, University of Texas, Austin TX 78712 USA

I have some big combinations like: 4444444444444444444444444444 choose 784645433 Can R compute these? Is there any package that does stirlings approximation in R? -- Thanks, Jim. [[alternative HTML version deleted]]

...are close to integers (within 1e-7). In those cases, k is silently rounded to integer. As I read your suggestion, n would only be rounded to integer if k > n-k. I think both n and k should be rounded to integer in this near-integer situation, regardless of the value of k. I believe that lchoose(n, k) already does this. Duncan Murdoch > > double r, k0 = k; > k = R_forceint(k); > ... > if (fabs(k - k0) > 1e-7) > MATHLIB_WARNING2(_("'k' (%.2f) must be integer, rounded to %.0f"), k0, k); > > >> Duncan Murdoch &...

...(within 1e-7). In those cases, k is silently rounded to integer. As I read your suggestion, n would only be rounded to integer if k > n-k. I think both n and k should be rounded to integer in this near-integer situation, regardless of the value of k. >>> >>> I believe that lchoose(n, k) already does this. >>> >>> Duncan Murdoch >>> >>>> double r, k0 = k; >>>> k = R_forceint(k); >>>> ... >>>> if (fabs(k - k0) > 1e-7) >>>> MATHLIB_WARNING2(_("'k' (%.2f) must...

...9 samples * Now to estimate the parameters, I first declared the negative log likelihood function of this new distribution as below(I used two methods, one with a loop and one without the loop) #without any loops *> Loglik.newdis1<- function(x,a,b,fre,n){ KBLL1<-sum(fre*(log(a*b)+lchoose(n,x)+log(sum((-1)**(0:1000) * choose(b-1, 0:1000) * beta(x+a+a*0:1000, n-x+1))))) return(-KBLL1) }* #here a and b are the parameters to be estimated and x=binomial values, fre=frequencies and n=binomial trials #and since the inner series is a convergent infinite series, a lar...

I have a 2 x 3 matrix called snp and I want to compute the following probability: choose(sum(snp[,1]), snp[1,1]) * choose(sum(snp[,2]), snp[1,2]) * choose(sum(snp[,3]), snp[1,3])/choose(sum(snp), sum(snp[1,])) but I keep getting Infs and NaNs. Is there a function that can do this in R? -- Thanks, Jim. [[alternative HTML version deleted]]

...integers (within 1e-7). In those cases, k is silently rounded to integer. As I read your suggestion, n would only be rounded to integer if k > n-k. I think both n and k should be rounded to integer in this near-integer situation, regardless of the value of k. >> >> I believe that lchoose(n, k) already does this. >> >> Duncan Murdoch >> >>> double r, k0 = k; >>> k = R_forceint(k); >>> ... >>> if (fabs(k - k0) > 1e-7) >>> MATHLIB_WARNING2(_("'k' (%.2f) must be integer, rounded to %.0f&quo...

1. lbeta and beta do not work properly: lbeta returns its first argument and beta gives the lbeta result. In names.c lines 245-6, the codes for these should be 2 and 3 instead of 1 and 2 2. crtl-C does not work (except the first time) on Red Hat elf Linux (which has many many other problems as well) nor on the previous version of Linux for Amiga. It worked on Slackware aout Linux and now works

1. lbeta and beta do not work properly: lbeta returns its first argument and beta gives the lbeta result. In names.c lines 245-6, the codes for these should be 2 and 3 instead of 1 and 2 2. crtl-C does not work (except the first time) on Red Hat elf Linux (which has many many other problems as well) nor on the previous version of Linux for Amiga. It worked on Slackware aout Linux and now works

This struck me as incorrect: > choose(3.999999, 4) [1] 0.9999979 > choose(3.9999999, 4) [1] 0 > choose(4, 4) [1] 1 > choose(4.0000001, 4) [1] 4 > choose(4.000001, 4) [1] 1.000002 Should base::choose(n, k) check whether n is within machine precision of k and return 1? Thanks, Erik *** sessionInfo() R version 3.6.0 beta (2019-04-15 r76395) Platform: x86_64-apple-darwin15.6.0