search for: rtmvnorm

Hello! I was wondering if it's possible to see the actual code of checkTmvArgs function that is part of the code for rtmvnorm (which is below - I just typed "rtmvnorm" on the prompt). I get an error: Error in checkTmvArgs(mean, sigma, lower, upper) : sigma must be a symmetric matrix At the same time I am pretty sure that the matrix I am passing as sigma is a var-covar matrix (however, it is NOT a correlation...

When sampling from a multi-variate truncated normal using rtmvnorm from the tmvnorm-package, I experience extreme performance differences between two of my computers. On my laptop computer, draws take ~5s, on my desktop ~30s. I need to run MCMCs with repeat calls to rtmvnorm on my desktop. The code in both cases is exactly the same. rtmvnorm seems not to have...

Hello! I am trying to generate a sample from a truncated multivariate normal distribution using rtmvnorm. I am using Gibbs because my alpha (line below) is teeny-tiny ( 4.083475e-64 ) alpha = pmvnorm(lower=lower, upper=upper, mean=btilde, sigma=MyVarCovar). When I try my Gibbs run, it takes quite a long time (with 10,000 iterations and 5,000 iterations burn-in) ~ 22 sec. And then what I get is all N...

Hi, dear all, I wish to get one sample (2500-d vector) from the truncated multivariate normal distribution, so I choose use the R function rtmvnorm() to do this. But the error information shows that for this function, the dimension should be lower than 1000, So could you help me to find out if there's any solution could do such sampling from a truncated multivariate normal distribution with the sigma dimension is 2500*2500?? Here is part...

I want to use the rtmvt from the {tmvtnorm} package using the "gibbs" algorithm but how to i specify the nested function rtmvnorm to use gibbs as well? Right now I am using the code: for (i in 1:g){ for (j in 1:n){ sgamma[,,i,j] = rtmvt(n=50, mean=mu[i,j], sigma[i,j], df=nu[i], lower=rep(0,2),algorithm="gibbs") } } heres an example of one iteration: > mu[1,1] -0.09734357 0.51578628 > sigma[1...

...bution, i.e. random number generation, density function, distribution functions like rtmvt(), dtmvt() und ptmvt() and ptmvt.marginal(). Random number generation supports both rejection sampling and Gibbs sampling. * We implemented a thinning technique for the Gibbs sampler in both rtmvt.gibbs() and rtmvnorm.gibbs(), including additional arguments "thinning", "start.value" and "burn.in" for controlling the Gibbs sampler. * We added a parameter "margin=NULL" to dtmvnorm() as an interface/wrapper to marginal density functions dtmvnorm.marginal() and dtmvnorm.margin...

I am sampling from the truncated multivariate student t distribution "rtmvt" in the package {tmvtnorm}. My question is about the mean vector. Is it possible to define a mean vector outside of the truncated region? Thank you in advance for any help. -- View this message in context: http://r.789695.n4.nabble.com/truncated-distributions-tp3422245p3422245.html Sent from the R help mailing

...bution, i.e. random number generation, density function, distribution functions like rtmvt(), dtmvt() und ptmvt() and ptmvt.marginal(). Random number generation supports both rejection sampling and Gibbs sampling. * We implemented a thinning technique for the Gibbs sampler in both rtmvt.gibbs() and rtmvnorm.gibbs(), including additional arguments "thinning", "start.value" and "burn.in" for controlling the Gibbs sampler. * We added a parameter "margin=NULL" to dtmvnorm() as an interface/wrapper to marginal density functions dtmvnorm.marginal() and dtmvnorm.margin...