similar to: rmultinom

Hi Mark: I had also used sample and tabulate for generating multinomial and found it to be quite slow. So I had written a multinomial random numbers generator based on the GENMUL subroutine from "ranlib", which in turn is based on the algorithm from Luc Devroye's book on "Non-Uniform Random Variate Generation" You may want to compare this with your hybrid algorithm and

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

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 successive

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

I've had a need for multinomial "random number generation" occasionally. And other people too. The following code is currently in the (very small ``not very high importance'') CRAN package normix --- which I will rename to "nor1mix" very seen because of a ``name registration'' problem I want to add "this" (well the functionality) to a

>>>>> 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,

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

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 probability vector > rmultinom(1, 3:5, c(1/2, 1/3, NA)) Error in rmultinom(1,

> On 10 Mar 2016, at 21:25 , M.van_Iterson at lumc.nl wrote: > > Hi all, > > I should have given a better explanation of my problem. Here it is. > > I extracted from my code the bit that gives the error. Place this in a file called test.c Aha. Missing info #1, C not R... > > #include <math.h> > #include <R.h> > #include <Rmath.h> >

// 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

Hi, I'm simulating a Markov chain in Fortran interfaced with R-2.2.1 in order to generate 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

Hi all, I should have given a better explanation of my problem. Here it is. I extracted from my code the bit that gives the error. Place this in a file called test.c #include <math.h> #include <R.h> #include <Rmath.h> #include <float.h> #include <R_ext/Print.h> int main(){ double prob[3] = {0.0, 0.0, 0.0}; double prob_tot = 0.; prob[0] = 0.3*dnorm(2, 0,

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

Dear R help I have been trying to conduct a chi square test on two groups of variables to test whether there is any relationship between the two sets of variables chisq.test(oxygen, train) Pearson's Chi-squared test data: oxygen X-squared = 26.6576, df = 128, p-value = 1 > chisq.test(oxygen) Pearson's Chi-squared test data: oxygen X-squared = 26.6576, df = 128,

Hello! I am having a problem understanding what the weights option in the locfit command of the locfit package is doing. I have written a sample program which illustrates the issue (below). The example involves using bootstrap however, that is not my main goal but it illustrates where my problem lies. As you know, to compute a bootstrap estimate of a particular quantity using a sample size of

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 sum to one close enough. I

Hola Jesús, Si no entiendo mal lo que planteas, has observado unas frecuencias N = c(12, 0, 8, 6, 4, 2) de pedidos acaecidos en 1:6 días, en total n = sum(N) pedidos. Llamemos P = (p1, p2, ?, p6) a las probabilidades ?teóricas? de pedido en cada día. En principio el vector N se puede considerar una realización de una distribución multinomial M(n; p1, ?, p6). P se puede estimar mediante las

R Experts: I am conducting a meta-analysis where the effect measures to be pooled are simple proportions. For example, consider this data from Fleiss/Levin/Paik's Statistical methods for rates and proportions (2003, p189) on smokers: Study N Event P(Event) 1 86 83 0.965 2 93 90 0.968 3 136 129 0.949 4 82 70 0.854 Total

>>>>> "Jacob" == Jacob van Wyk <jlvw at rau.ac.za> writes: Jacob> Could anybody please help: I simply want to generate Jacob> random samples from a multinomial distribution with Jacob> fixed n and given probability vector p. Jacob> How can I do this? I've recently written the following {for the R package "normix"}. The

I present you with a function that solves a problem that has bugged me for many years. I think the problem may be general enough to at least consider adding this function, or a revamped version of it, to the 'stats' package, with the other multinomial functions reside. I'm using R to export data to text files, which are input data for an external model written in C++. Parts of the