Package: densEstBayes
Version: 1.0-2.2
Date: 2021-08-19
Title: Density Estimation via Bayesian Inference Engines
Authors@R: person("Matt P.", "Wand", role = c("aut","cre"),
                  email = "matt.wand@uts.edu.au",
                  comment = c(ORCID = "0000-0003-2555-896X"))
Maintainer: Matt P. Wand <matt.wand@uts.edu.au>
Description: 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) <arXiv:2009.06182>.
License: GPL (>= 2)
LazyData: true
Biarch: true
Depends: R (>= 3.5.0)
Imports: MASS, nlme, Rcpp, methods, rstan, rstantools
LinkingTo: BH, Rcpp, RcppArmadillo, RcppEigen, RcppParallel,
        StanHeaders, rstan
SystemRequirements: GNU make
NeedsCompilation: yes
Packaged: 2023-03-30 08:37:26 UTC; andrew
Author: Matt P. Wand [aut, cre] (<https://orcid.org/0000-0003-2555-896X>)
Repository: CRAN
Date/Publication: 2023-03-31 06:43:36 UTC
Built: R 4.6.0; x86_64-apple-darwin20; 2026-04-30 06:35:11 UTC; unix
Archs: densEstBayes.so.dSYM
