dsample: Discretization-Based Direct Random Sample Generation

Discretization-based random sampling algorithm that is useful for a complex model in high dimension is implemented. The normalizing constant of a target distribution is not needed. Posterior summaries are compared with those by 'OpenBUGS'. The method is described: Wang and Lee (2014) <doi:10.1016/j.csda.2013.06.011> and exercised in Lee (2009) <http://hdl.handle.net/1993/21352>.

Imports: stats, graphics, MASS, mnormt
Suggests: knitr, rmarkdown
Published: 2023-02-09
Author: Chel Hee Lee ORCID iD [aut, cre], Liqun Wang [aut]
Maintainer: Chel Hee Lee <chelhee.lee at ucalgary.ca>
License: GPL-3
NeedsCompilation: no
Materials: README
CRAN checks: dsample results


Reference manual: dsample.pdf
Vignettes: example


Package source: dsample_0.91.3.4.tar.gz
Windows binaries: r-devel: dsample_0.91.3.4.zip, r-release: dsample_0.91.3.4.zip, r-oldrel: dsample_0.91.3.4.zip
macOS binaries: r-release (arm64): dsample_0.91.3.4.tgz, r-oldrel (arm64): dsample_0.91.3.4.tgz, r-release (x86_64): dsample_0.91.3.4.tgz, r-oldrel (x86_64): dsample_0.91.3.4.tgz
Old sources: dsample archive


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