similar to: tmvtnorm: version 1.0-2

Dear R users, the tmvtnorm package, the package for the truncated multivariate normal distribution, has been updated on CRAN. The major changes in version 0.8 are: * Reimplemented the Gibbs' sampler for random number generation in Fortran for performance reasons. This compiled code is now even faster than conventional rejection sampling and allows for the generation of large amounts of

Dear R users, the tmvtnorm package, the package for the truncated multivariate normal distribution, has been updated on CRAN. The major changes in version 0.8 are: * Reimplemented the Gibbs' sampler for random number generation in Fortran for performance reasons. This compiled code is now even faster than conventional rejection sampling and allows for the generation of large amounts of

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: >

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

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

This Article describes installation of some packages from EPEL (section 6.1). Listed in the packages to include is java-1.6.0-openjdk*. I think this is not necessary anymore as java-1.6.0-openjdk* is part of CentOS 5 now. financial.com AG Munich head office/Hauptsitz M?nchen: Maria-Probst-Str. 19 | 80939 M?nchen | Germany Frankfurt branch office/Niederlassung Frankfurt: Messeturm |

In the sudo section please add "sudo -s" and "sudo -i" as ways to open a root-shell. Chris financial.com AG Munich head office/Hauptsitz M?nchen: Maria-Probst-Str. 19 | 80939 M?nchen | Germany Frankfurt branch office/Niederlassung Frankfurt: Messeturm | Friedrich-Ebert-Anlage 49 | 60327 Frankfurt | Germany Management board/Vorstand: Dr. Steffen Boehnert (CEO/Vorsitzender) |

Is it ok if I add elrepo references to HowTos/Custom_Kernel and AdditionalResources/Repositories? Chris financial.com AG Munich head office/Hauptsitz M?nchen: Maria-Probst-Str. 19 | 80939 M?nchen | Germany Frankfurt branch office/Niederlassung Frankfurt: Messeturm | Friedrich-Ebert-Anlage 49 | 60327 Frankfurt | Germany Management board/Vorstand: Dr. Steffen Boehnert (CEO/Vorsitzender) | Dr.

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], df=ceiling(nu[i]+p), lower=c(0,0), algorithm="gibbs") Any

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

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

>>>>> David Winsemius <dwinsemius at comcast.net> >>>>> on Tue, 9 May 2017 14:33:04 -0700 writes: >> On May 9, 2017, at 2:05 PM, Czarek Kowalski <czarek230800 at gmail.com> wrote: >> >> I have already posted that in attachement - pdf file. > I see that now. I failed to scroll to the 3rd page. from a late reader:

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 any machine dependent defaults

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

On Thu, 2018-04-19 at 07:59 -0500, Valeri Galtsev wrote: > Aha, now I understand what you want. It probably doesn't exist on > master repository server. You can re-master DVD from two of them or > from a copy of content of both in some directory on hard drive. Unsure how to remaster two DVDs, total 6GB?, onto a USB stick. I can copy both DVDs to a directory. To make the directory

> Aha, now I understand what you want. It probably doesn't exist on > master repository server. You can re-master DVD from two of them or > from a copy of content of both in some directory on hard drive. Unsure how to remaster two DVDs, total 6GB?, onto a USB stick. I can copy both DVDs to a directory. To make the directory contents into a single ISO is, currently, beyond my

I am using both nlminb and optim to get MLEs from a likelihood function I have developed. AFAIK, the model I has not been previously used in this way and so I am struggling a bit to unit test my code since I don't have another data set to compare this kind of estimation to. The likelihood I have is (in tex below) \begin{equation} \label{eqn:marginal} L(\beta) = \prod_{s=1}^N \int

I am receiving the above error ( full r session output below) the script runs OK in windows. and "genotypes" and "ploidy" are both correct arguments any suggestions would be most welcome Nevil Amos MERG/ACB Monash University School of Biological Sciences > library(Geneland) Loading required package: RandomFields Loading required package: fields Loading required

Hi All, I'm trying to use the geoRglm package to run a poisson spatial glm on a dataset with several covariates. When I run without covariates I have no problems. control1.data.geo <- mcmc.control(S.scale=0.2, thin = 1) model1.data.geo <- list(cov.pars = c(1,1), beta=c(1), family="poisson") test1.model1 <- glsm.mcmc(data.geo, model=model1.data.geo,

Anybody interested in the S maps library for R? I have ported a limited version of the software for a Unix platform, and would be happy to make it available for anybody interested. If there is a lot of interest then I will submit it to CRAN. I know that Ross Ihaka is working on a new version for R, which does not have some of the limitations of the original S version. My version does not do