How to Install and Uninstall R-tmvnsim.x86_64 Package on Fedora 34
Last updated: November 17,2024
1. Install "R-tmvnsim.x86_64" package
Please follow the guidance below to install R-tmvnsim.x86_64 on Fedora 34
$
sudo dnf update
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$
sudo dnf install
R-tmvnsim.x86_64
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2. Uninstall "R-tmvnsim.x86_64" package
Please follow the instructions below to uninstall R-tmvnsim.x86_64 on Fedora 34:
$
sudo dnf remove
R-tmvnsim.x86_64
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$
sudo dnf autoremove
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3. Information about the R-tmvnsim.x86_64 package on Fedora 34
Last metadata expiration check: 0:35:31 ago on Tue Sep 6 14:10:38 2022.
Available Packages
Name : R-tmvnsim
Version : 1.0.2
Release : 3.fc34
Architecture : x86_64
Size : 31 k
Source : R-tmvnsim-1.0.2-3.fc34.src.rpm
Repository : fedora
Summary : Truncated Multivariate Normal Simulation
URL : https://CRAN.R-project.org/package=tmvnsim
License : GPLv2
Description : Importance sampling from the truncated multivariate normal using the GHK
: (Geweke-Hajivassiliou-Keane) simulator. Unlike Gibbs sampling which can get
: stuck in one truncation sub-region depending on initial values, this package
: allows truncation based on disjoint regions that are created by truncation of
: absolute values. The GHK algorithm uses simple Cholesky transformation followed
: by recursive simulation of univariate truncated normals hence there are also no
: convergence issues. Importance sample is returned along with sampling weights,
: based on which, one can calculate integrals over truncated regions for
: multivariate normals.
Available Packages
Name : R-tmvnsim
Version : 1.0.2
Release : 3.fc34
Architecture : x86_64
Size : 31 k
Source : R-tmvnsim-1.0.2-3.fc34.src.rpm
Repository : fedora
Summary : Truncated Multivariate Normal Simulation
URL : https://CRAN.R-project.org/package=tmvnsim
License : GPLv2
Description : Importance sampling from the truncated multivariate normal using the GHK
: (Geweke-Hajivassiliou-Keane) simulator. Unlike Gibbs sampling which can get
: stuck in one truncation sub-region depending on initial values, this package
: allows truncation based on disjoint regions that are created by truncation of
: absolute values. The GHK algorithm uses simple Cholesky transformation followed
: by recursive simulation of univariate truncated normals hence there are also no
: convergence issues. Importance sample is returned along with sampling weights,
: based on which, one can calculate integrals over truncated regions for
: multivariate normals.