search for: rtmvt

I have been using the rtmvt function in the {tmvtnorm} package i'm getting the warning: "Acceptance rate is very low and rejection sampling becomes inefficient. Consider using Gibbs sampling." but i AM specifying the gibbs algorithm!!: rtmvt(M, mean=q[,,i,j], sigma=((u[i,j] + nu[i])/(p+nu[i]))*delta[,,i],...

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),algorit...

Dear Members, I am working with 6-dimensional Student-t distribution with 4 degrees of freedom truncated to [20; 60]. I have generated 100 000 samples from truncated multivariate Student-t distribution using rtmvt function from package ?tmvtnorm?. I have also calculated mean vector using equation (3) from attached pdf. The problem is, that after summing all elements in one column of rtmvt result (and dividing by 100 000) I do not receive the same result as using (3) equation. Could You tell me, what is inco...

...6, -6, -2, 12, >> 0, -6, 4, 2, -2, -5, >> 2, -6, 2, 25, 0, -17, >> -1, -2, -2, 0, 9, -5, >> -1, 12, -5, -17, -5, 36), 6, 6) >> df = 4 >> lower = c(20, 20, 20, 20, 20, 20) >> upper = c(60, 60, 60, 60, 60, 60) >> X1 <- rtmvt(n=100000, meann, covv, df, lower, upper) >> >> >>> sum(X1[,1]) / 100000 >> [1] 54.98258 >> sum(X1[,2]) / 100000 >> [1] 40.36153 >> sum(X1[,3]) / 100000 >> [1] 49.83571 >> sum(X1[,4]) / 100000 >>...

...ted multivariate normal and Student-t distribution, has been updated on CRAN. The major changes in version 1.0-2 (2010-03-04) are: * The package now provides methods for the truncated multivariate Student-t distribution, 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&q...

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...

...ted multivariate normal and Student-t distribution, has been updated on CRAN. The major changes in version 1.0-2 (2010-03-04) are: * The package now provides methods for the truncated multivariate Student-t distribution, 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&q...