Package: hdtg
Title: Generate Samples from Multivariate Truncated Normal
        Distributions
Version: 0.3.4
Authors@R: 
  c(person("Zhenyu", "Zhang", email = "zhangzhenyusa@gmail.com", role = c("aut", "cre")),
    person("Andrew", "Chin", email = "achin23@jhu.edu", role = "aut"),
    person("Akihiko", "Nishimura", email = "akihiko4@gmail.com", role = "aut"),
    person("Marc A.", "Suchard", email = "msuchard@ucla.edu", role = "aut"),
    person("John W.", "Ratcliff et al.", role = c("cph", "ctb"),
      comment = "authors and copyright holders of see2neon.h under an MIT license"))
Maintainer: Zhenyu Zhang <zhangzhenyusa@gmail.com>
Description: 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 (2024) <doi:10.1080/01621459.2024.2395587>, and  harmonic Monte Carlo in Ari Pakman 
 and Liam Paninski (2014) <doi:10.1080/10618600.2013.788448>.
License: MIT + file LICENSE
Encoding: UTF-8
RoxygenNote: 7.3.3
Imports: Rcpp, RcppParallel, mgcv, Rdpack
RdMacros: Rdpack
LinkingTo: Rcpp, RcppEigen, RcppParallel
Suggests: TruncatedNormal, testthat (>= 3.0.0)
Config/testthat/edition: 3
SystemRequirements: CPU with AVX/SSE4.2 (optional for better
        performance)
Acknowledgements: The package uses the following R infrastructure: Rcpp
        (Eddelbuettel & Francois, 2011), RcppEigen (Bates &
        Eddelbuettel, 2013), RcppParallel (Allaire et al., 2025), mgcv
        (Wood, 2017), and Rdpack (Boshnakov, 2023).
NeedsCompilation: yes
Packaged: 2026-02-11 12:37:23 UTC; zhenyu
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)
Repository: CRAN
Date/Publication: 2026-02-11 14:10:02 UTC
Built: R 4.6.0; aarch64-apple-darwin23; 2026-04-26 03:51:55 UTC; unix
Archs: hdtg.so.dSYM
