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: Downloads: Reverse dependencies: Linking:Please use the canonical form https://CRAN.R-project.org/package=densEstBayes to link to this page.
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