Package: densEstBayes
Version: 1.0-1
Date: 2020-09-28
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
LinkingTo: BH, Rcpp, RcppArmadillo, RcppEigen, RcppParallel,
        StanHeaders, rstan
SystemRequirements: GNU make
NeedsCompilation: yes
Packaged: 2020-09-27 21:42:01 UTC; mwand
Author: Matt P. Wand [aut, cre] (<https://orcid.org/0000-0003-2555-896X>)
Repository: CRAN
Date/Publication: 2020-09-30 08:50:05 UTC
Built: R 4.0.2; x86_64-apple-darwin17.0; 2020-10-01 11:36:35 UTC; unix
Archs: densEstBayes.so.dSYM
