search for: rmultinom

>>>>> Christophe Dutang >>>>> on Sat, 8 Apr 2023 14:21:53 +0200 writes: > Dear all, > Using rmultinom() in a stochastic model, I found this function returns an error message 'NA in probability' for an infinite probability. > Maybe, a more precise message will be helpful when debugging. >> rmultinom(1, 3:5, c(1/2, 1/3, Inf)) > Error in rmultinom(1, 3:5, c(1/2, 1/3...

On 08/04/2023 5:53 p.m., Martin Maechler wrote: >>>>>> Christophe Dutang >>>>>> on Sat, 8 Apr 2023 14:21:53 +0200 writes: > > > Dear all, > > > Using rmultinom() in a stochastic model, I found this function returns an error message 'NA in probability' for an infinite probability. > > > Maybe, a more precise message will be helpful when debugging. > > >> rmultinom(1, 3:5, c(1/2, 1/3, Inf)) > > Error in rm...

Dear all, Using rmultinom() in a stochastic model, I found this function returns an error message 'NA in probability' for an infinite probability. Maybe, a more precise message will be helpful when debugging. > rmultinom(1, 3:5, c(1/2, 1/3, Inf)) Error in rmultinom(1, 3:5, c(1/2, 1/3, Inf)) : NA in probabili...

...erate data according to a Markov Random Field called the Potts model. R Version: platform i686-pc-linux-gnu arch i686 os linux-gnu system i686, linux-gnu status major 2 minor 2.1 year 2005 month 12 day 20 svn rev 36812 Each loop of my Fortran calls the function rmultinom.c of the R's Random Number Generator through the wrapper: #include <R.h> #include <Rmath.h> void F77_SUB(sarmultinom)(int n, double* prob, int K, int* rN){ rmultinom(n, prob, K, rN);} My fortran progr...

...or(int j = 0; j < 3; j++) prob[j] = prob[j]/prob_tot; //or this give the same error //prob[2] = 1.0 - prob[1] - prob[0]; //checking indeed prob_tot not exactly 1 for(int j = 0; j < 3; j++) prob_tot += prob[j]; Rprintf("Prob_tot: %f\n", prob_tot); int rN[3]; rmultinom(1, prob, 1, rN); return 0; } run R CMD SHLIB test.c to generate the test.so. Now from within R > dyn.load("test.so") > .C("main") Prob_tot: 1.017084 Error: rbinom: probability sum should be 1, but is 0.948075 Maybe I miss some trivial C knowledge why this is not exac...

...hm from Luc Devroye's book on "Non-Uniform Random Variate Generation" You may want to compare this with your hybrid algorithm and see their relative performance. Best, Ravi. ############################################################### ## A multinomial random vector generator rmultinom <- function(n, p){ ncat <- length(p) # Check Arguments if (n < 0) {cat("n < 0 ","\n"); break} if (ncat <= 1) {cat("ncat <= 1 ","\n"); break} if (any(p < 0.0)) {cat("Some P(i) < 0 ","\n"); brea...

Dear newsgroup, There was a recent post suggesting the incorporation of a standard rmultinom(...). This seems like a good idea, but I wasn't sure about basing this on tabulate( sample( ...)). Despite the attractive succinctness, this could be very slow and use lots of memory if n or size is large. Instead, I've tended to use a loop over the boxes of the multinomial, taking successi...

// R 2.3.1 Can someone please explain why this error returns? > y=numeric(100) > x=matrix(runif(16),4,4) > for(i in 2:100) + { + y[i]=which(rmultinom(1, size = 1, prob = x[y[i-1], ])==1) + } Error in rmultinom(n, size, prob) : too few positive probabilities thx much ej

...s give the same error > //prob[2] = 1.0 - prob[1] - prob[0]; > prob_tot = 0; missing here > //checking indeed prob_tot not exactly 1 > for(int j = 0; j < 3; j++) > prob_tot += prob[j]; > > Rprintf("Prob_tot: %f\n", prob_tot); > > int rN[3]; > rmultinom(1, prob, 1, rN); Er, where do you tell rmultinom that variates are three-dimensional? It's not going to infer it from array sizes. -pd > return 0; > } > > run R CMD SHLIB test.c to generate the test.so. Now from within R > >> dyn.load("test.so") >> .C...

Dear all, I have a questions regarding using the c function rmultinom.c. I got the following error message "rbinom: probability sum should be 1, but is 0.999264" Which is thrown by: if(fabs((double)(p_tot - 1.)) > 1e-7) MATHLIB_ERROR(_("rbinom: probability sum should be 1, but is %g"), (double) p_tot); I understand my probabilities do not...

Hi Can anyone help me? I am not an experienced R user (or statistician!). If I use rmultinom to generate random outcomes of a multinomial distribution, how do i use these in a way to help conduct an exact chi-squared test? woozles48 -- View this message in context: http://www.nabble.com/rmultinom-tf3626954.html#a10127600 Sent from the R help mailing list archive at Nabble.com.

...t it: but i get this error message. i hope someone can help me. Error in dim(robj) <- c(dX, dY) : dims [product 16] do not match the length of object [1] p_11=seq(0,0.3,0.1) p_12=seq(0.1,0.4,0.1) guete = function(p_11,p_12) { set.seed(1000) S_vek=matrix(0,nrow=N,ncol=1) for(i in 1:N) { X_0=rmultinom(q-1,size=1,prob=p_0) X_1=rmultinom(n-q+1,size=1,prob=cbind(p_11,p_12,(1-p_11-p_12))) N_0=apply(X_0[,(n-2*k-L+1):(n-k-L)],1,sum) N_1=apply(X_1[,(n-q-k+2):(n-q+1)],1,sum) S_vek[i]=((sum(((N_1-k*cbind(p_11,p_12,(1-p_11-p_12)))^2)/k*cbind(p_11,p_12,(1-p_11-p_12))))/(sum(((N_0-k*p_0)^2)/k*p_0)))-1 } 1-m...

Dear R users, This is a problem that has puzzled me for quite some time, and I wonder if anyone could offer me an insight to what is happening? I generated a multinomial matrix by using A<-rmultinom(100,1,c(0.4,0.3,0.2,0.1), and multiply this matrix by a set of values say B<-runif(n,100,50). I then calculate var(colSums(A*B)). I was able to work out the theoretical mean of var(colSums(A*B)) by using fun.var.match.gen below. I was however not sure, why is there a persistent over estimate...

On 10 Mar 2016, at 12:47 , M.van_Iterson at lumc.nl wrote: > Dear all, > > I have a questions regarding using the c function rmultinom.c. > > I got the following error message "rbinom: probability sum should be 1, but is 0.999264" > > Which is thrown by: > > if(fabs((double)(p_tot - 1.)) > 1e-7) > MATHLIB_ERROR(_("rbinom: probability sum should be 1, but is %g"), > (double) p_tot);...

...probTrt=matrix(0,4,3); probTrt; #malf, death, normal probTrt[1,]=c(0.064,0.119,0.817);#for Trt 1 probTrt[2,]=c(0.053,0.125,0.823);#for Trt 2 probTrt[3,]=c(0.111,0.139,0.750);#for Trt 3 probTrt[4,]=c(0.351,0.364,0.285);#for Trt 4 for (t in 4){ assign(paste("Trt",t,sep=""),rmultinom(10, size = 5, prob=probTrt[t,])); } But the following does not work. for (t in 4){ assign(paste("Trt",t,sep=""),rmultinom(10, size = 5, prob=probTrt[t,])); rowMeans(paste("Trt",t,sep="")); } How can I use it in functions like rowM...

...TH (Federal Inst. Technology) 8092 Zurich SWITZERLAND phone: x-41-1-632-3408 fax: ...-1228 <>< ## This is based on rmultz2() from S-news by Alan Zaslavsky & Scott Chasalow; ## in R available from library(combinat) -- but it has ## Arg.names like rbinom(); returns n x p matrix rmultinom <- function(n, size, prob) { K <- length(prob) # #{classes} matrix(tabulate(sample(K, n * size, repl = TRUE, prob) + K * 0:(n - 1), nbins = n * K), nrow = n, ncol = K, byrow = TRUE) }

...Aa.control <- 2*p.control*q.control # P(G=Aa) # p.AA.control <- q.control^2 # P(G=AA) # ################################### ##### Generating Control Data ##### ################################### ## Minor Allele Frequency ## for (h in 1:800) { datamat[h,] <- t(rmultinom(1, size=c(10, 40, 50), prob=c(0.33, 0.33, 0.34))) } for (h in 801:1000) { datamat[h,] <- t(rmultinom(1, size=c(10,40,50), prob=c(p.aa.control[h], p.Aa.control[h], p.AA.control[h]))) } list.treat[[k]] <- datamat } -- Thanks, Jim. [[alternative HTML version deleted]]

...ationb2[1,2]<-sample(1:6, 1, prob=w, repl=T) i<-1;observationb3[1,2]<-sample(1:6, 1, prob=w, repl=T) i<-1;observationb4[1,2]<-sample(1:6, 1, prob=w, repl=T) while(i<n+1){ stateb1<-observationb1[i,2]; probsb1<-transitions[stateb1,1:6]; nextstateb1<-rmultinom(1,1,probsb1); seqb1<-which.max(nextstateb1); j<-i+1; observationb1[j,2]<-seqb1;i<-j #-------------------------------------if I close the brackets here this works but I want to inlcude this next bit of code for bird 2 stateb2<-observationb2[i,2]; pr...

Dear list members, I have a series of /unequal/ probabilities [p1,p2,...,pk], describing mutually exclusive events, and a "remainder" class with a probability p0=1-p1-p2-....-pk, and need to calculate, for a given number of trials t>=k, the combined probability that each of the classes 1...k contains at least 1 "event" (the remainder class may be empty). To me this reaks

Hey everyone, I am at best, an amateur user of R, but I am stuck on how to set-up the following situation. I am trying to select a random sample of numbers from 0 to 10 and insert them into the first column of a matrix (which will used later in a loop). However, I need to have those numbers add up to 10. How can I set those conditions? So far I have: n<-matrix(0,nr=5,ncol=10) for(i in