similar to: multivariate random variable

Hi all, I am imputing missingness of  90 columns  in a  data frame using mice. But "mice" gives back :  Error in nnet.default(X, Y, w, mask = mask, size = 0, skip = TRUE, softmax = TRUE,  :   too many (1100) weights Any idea to solve this error is welcome, Anera [[alternative HTML version deleted]]

Hi all, I am trying to fit a random effect  model to categorical response variable using package "ordinal" /"clmm". How can I find the correlation between random effects (random intercept and random slope)   Thanks in advance  Ana [[alternative HTML version deleted]]

  I am trying to used "ordgee" from "geepack" for an ordinal dataset. When I write the code it returns  "Warning message:In binomial(link) : use of binomial(link=link) is deprecated" , but the program runs. Even when I run your example for "ohio" and "respdis", it returns the same error. Please guide me [[alternative HTML version deleted]]

Sir, I want to draw random from any multivariate disrtibution. Is there any function in R to do this? Regards, Suman Dhara [[alternative HTML version deleted]]

Dear All, Is there any function in R for computing "multivariate chi-square distribution"? How about "multivariate gamma distribution"? I appreciate any comment on this subject. Thank you, Amin Zollanvari PhD student Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX

Hello, from a search of the archives and functions, I am looking for information on creating random correlated counts from a multivariate Poisson distribution.  I can not seem to find a function that does this. Perhaps, it has not yet  been created. Has anyone created an R package that does this.   thanks,   Jourdan Gold     [[alternative HTML version deleted]]

I have the following function, a MSE calc based on some Multivariate normals: MV.MSE<-function(n,EP,X,S){ (dmvnorm(X,mean=rep(0,2),I+S+EP)-dmvnorm(X,mean=rep(0,2),I+S))^2 + 1/n*(dmvnorm(X,mean=rep(0,2),1+S+EP/2)*det(4*pi*EP)^-.5- (dmvnorm(X,mean=rep(0,2),I+S+EP ))^2)} I can get the MV.MSE for given values of the function e.g

Hello, I would like to simulate randomly from a multivariate normal distribution using a correlation matrix, rho. I do not have sigma. I have searched the help archive and the R documentation as well as doing a standard google search. What I have seen is that one can either use rmvnorm in the package: mvtnorm or mvrnorm in the package: MASS. I believe I read somewhere that the latter was

Dear All, I am using the pmst function from the sn package (version 0.4-0). After inserting the example from the help page, I get non-trivial answers, so everything is fine. However, when I try to extend it to higher dimension: xi <- alpha <- x <- rep(0,27) Omega <- diag(0,27) p1 <- pmst(x, xi, Omega, alpha, df = 5) I get the following result: >p1 [1] 0 attr(,"error")

I am using curve3d in the emdbook package to graph a gaussian copula density function generated via the copula package. Unfortunately, it appears that emdbook masks dmvnorm from the package mvtnorm in a way that prohibits copula from generating the gaussian copula. (Sounds very confusing!) For example, > library(copula) > f<-function(x,y) dcopula(normalCopula(0),c(x,y)) >

Does anybody know of a function that implements the derivative (gradient) of the multivariate normal density with respect to the *parameters*? It?s easy enough to implement myself, but I?d like to avoid reinventing the wheel (with some bugs) if possible. Here?s a simple example of the result I?d like, using numerical differentiation: library(mvtnorm) library(numDeriv) f=function(pars, xx, yy)

Hello all... I am just starting to teach myself Bayesian methods, and am interested in learning how to use UMacs. I've read the documentation, but the single example is a bit over my head at the level I am at right now. I was wondering if anyone has any simple examples they'd like to share. I've successfully done a couple of simple gibbs examples, but have had a hard time

Hi, I am looking for an efficient way to compute the values of the density function of a multivariate T distribution - something like "dmvnorm", but for T distr. Does this exist somewhere? Many thanks, Jan Bulla Goettingen University

Hi, I would like to know, if there's any R function, which allows calculation of probability values (0,1) from multivariate normal densities. I would be grateful for any output. Cheers, MG

Dear?All, ? a few weeks ago I have posted a question on the R help listserv that?some of you have responded to with a great solution, would like to thank you for that? again.?I thought I would reach out to you with the issue I am trying to solve now. I have posted the question a few days ago, but probably it was not?clear enough, so I thought i try it again.?At times I have a multivariate example

Does anyone know of a package that uses C code to calculate a multivariate normal density? My goal is to find a faster way to calculate MVN densities and avoid R loops or apply functions, such as when X and mu are N x K matrices, as opposed to vectors, and in this particular case, speed really matters. I would like to be able to use .C or .Call to pass X, mu, Sigma, and N to a C program and have

Hello Anyone that now of any function in R that can calculate copulas? Or if anyone have any code avaible I would be more than interested. Thank you in advance /Thomas ______________________________________________ R-help at stat.math.ethz.ch mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help

Hi, Do any body know which packages of R I need to go for the below topics? 1. Monte Carlo Markov chain (MCMC) 2. Gibbs Sampling 3. Metropolis Hastings Thanks in advance... Shubha [[alternative HTML version deleted]]

Hello, In my simulations, I have to use the values of the cumulative distribution function of a multivariate normal with known mean vector and dispersion matrix. Please, can you tell me if there is a package in R to do that? Thank you very much for your greatly appreciate cooperation. Bernard Colin Colin Bernard Professeur titulaire Département de Mathématiques Faculté des Sciences Université

Announcement: mvtnorm Multivariate Normal and T Distribution mvtnorm implements two R functions for the computation of the multivariate t and normal distribution: pmvt: Computes the the distribution function of the multivariate t distribution for arbitary limits, degrees of freedom and correlation matrices based on algorithms by Genz and Bretz. pmvnorm: Computes the distribution