similar to: Sampling with conditions

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

>>>>> 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,

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,

Hello, i wrote this function guete and now i want to plot 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)

Hello Listers, I am trying to sample a vector to create a new one of sample length, witha sum equal to the sum of the initial vector: initial = 10, 30, 10 (sum=50) sample example = 5, 35, 10 (sum=50) or 25, 15, 10 (sum=50), etc ... My problem is to control the sum, so it stays constant. Any suggestions would be very helpful ! Thank you in advance, Eric

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

Hello, I'm having trouble in using "assign(paste ..." command . I could create several dataframes following trinomial distribution using it but it could not be used to check their row means of the created dataframe. For example, the following works: 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

// 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

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

Dear All, I would like to generate m positive real numbers c_i, I=1,...,m, such that (1) c_1 + c_2 + ... + c_m=m, (1) after being ordered into c_1 >= c_2 >= .... >=c_m>0, we have that c_m is of the same order of m^(-1/8), when m is sufficiently large. Thanks, -Chee [[alternative HTML version deleted]]

Saludos compañeros/as. Consideren una matriz de n columnas y n filas. Quiero distribuir aleatoriamente 6 números predefinidos (11,12,13,21,22,23,31,32,33,41,42,43), con una probabilidad de aparición de cada número que será igual a la frecuencia de ese número dividida por la frecuencia total de todos los números. Soy incapaz de resolver el problema: con la función rbinom sólo puedo generar dos

Hi, I am trying to write a simulation of the movements of four animals between six patches. The movement between patches is based on a first-order Markov chain so that the next patch they visit depends on the patch they were in before. I have written code that allows me to simulate the movement of one animal but when I add more there seems to be a problem and all chains come back as N/A. I can

(apologies for the cross-posting, and for this being a more general stats question rather than a specific-to-R one. I assure you I will be doing the actual analysis in R :) I am trying to determine the distribution and variance for a classic stochastic (transition) matrix problem such that: let x(t) be an initial state vector consisting of counts of classes A, B and C: x(t) =

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

Dear List, My first R function is a rip-off bagging algorithm from pg. 138 of Everitt and Hothorn's "Handbook of Statistical Analyses using R" (HSAUR). I'm using recursive partitioning to develop a set of useful variables in diagnosing ADHD. I'm running this in ESS in XEmacs 21.4.19, R 2.4.1 on Slackware Linux 11.0 with a 2.6 kernel. This is almost an entire script,

Hello, I am trying to simulate 10 relicates of 100-tables. Each table is a 2 x 3 and 80% pf the tables are true nulls and 20% are non-nulls. The nulls follow the Hardy Weinberg distribution (ratio) 1:2:1. I have the code below but the p-values are not what I am expecting. I want to use the Cochran Armitage trend test to get the p-values. num.reps=10 num.vars=1000 pi0 = 80 num.subjects = 100

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

After scouring the online R resources and help pages, I still need clarification on the function rmultinomial(). I would like to create a vector, say of 100 elements, where every element in the vector can take on the value of 0, 1 or 2, and where each of those values have a specific probability. ie. the probability a given element in the vector = 0 is 0.06, 1 = 0.38, 2 = 0.56 (probabilities sum