densEstBayes: Density Estimation via Bayesian Inference Engines

Bayesian density estimates for univariate continuous random samples are provided using the Bayesian inference engine paradigm. The engine options are: Hamiltonian Monte Carlo, the no U-turn sampler, semiparametric mean field variational Bayes and slice sampling. The methodology is described in Wand and Yu (2020) <doi:10.48550/arXiv.2009.06182>.

Version:	1.0-2.2
Depends:	R (≥ 3.5.0)
Imports:	MASS, nlme, Rcpp, methods, rstan, rstantools
LinkingTo:	BH, Rcpp, RcppArmadillo, RcppEigen, RcppParallel, StanHeaders, rstan
Published:	2023-03-31
DOI:	10.32614/CRAN.package.densEstBayes
Author:	Matt P. Wand [aut, cre]
Maintainer:	Matt P. Wand <matt.wand at uts.edu.au>
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation:	yes
SystemRequirements:	GNU make
In views:	Bayesian
CRAN checks:	densEstBayes results

Documentation:

Reference manual:	densEstBayes.pdf
Vignettes:	densEstBayes User Manual

Downloads:

Package source:	densEstBayes_1.0-2.2.tar.gz
Windows binaries:	r-devel: densEstBayes_1.0-2.2.zip, r-release: densEstBayes_1.0-2.2.zip, r-oldrel: densEstBayes_1.0-2.2.zip
macOS binaries:	r-release (arm64): densEstBayes_1.0-2.2.tgz, r-oldrel (arm64): densEstBayes_1.0-2.2.tgz, r-release (x86_64): densEstBayes_1.0-2.2.tgz, r-oldrel (x86_64): densEstBayes_1.0-2.2.tgz
Old sources:	densEstBayes archive

Reverse dependencies:

Reverse imports:	reldist
Reverse suggests:	sspse

Linking:

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