hdtg: Generate Samples from Multivariate Truncated Normal Distributions

Efficient sampling from high-dimensional truncated Gaussian distributions, or multivariate truncated normal (MTN). Techniques include zigzag Hamiltonian Monte Carlo as in Akihiko Nishimura, Zhenyu Zhang and Marc A. Suchard (2021) <arXiv:2104.07694>, and harmonic Monte in Ari Pakman and Liam Paninski (2014) <doi:10.1080/10618600.2013.788448>.

Version: 0.2.0
Imports: Rcpp, RcppParallel, RcppXsimd, mgcv, stats, Rdpack
LinkingTo: Rcpp, RcppEigen, RcppParallel, RcppXsimd
Published: 2022-08-07
Author: Zhenyu Zhang [aut, cre], Andrew Chin [aut], Akihiko Nishimura [aut], Marc A. Suchard [aut], John W. Ratcliff et al. [cph, ctb] (authors and copyright holders of see2neon.h under an MIT license)
Maintainer: Zhenyu Zhang <zhangzhenyusa at gmail.com>
License: MIT + file LICENSE
NeedsCompilation: yes
SystemRequirements: C++14
Citation: hdtg citation info
CRAN checks: hdtg results


Reference manual: hdtg.pdf


Package source: hdtg_0.2.0.tar.gz
Windows binaries: r-devel: hdtg_0.2.0.zip, r-release: hdtg_0.2.0.zip, r-oldrel: hdtg_0.2.0.zip
macOS binaries: r-release (arm64): hdtg_0.2.0.tgz, r-oldrel (arm64): hdtg_0.2.0.tgz, r-release (x86_64): hdtg_0.2.0.tgz, r-oldrel (x86_64): hdtg_0.2.0.tgz
Old sources: hdtg archive


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