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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) <arXiv:2009.06182>.
Getting started
Browse package contents
Package details |
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| Author | Matt P. Wand [aut, cre] (<https://orcid.org/0000-0003-2555-896X>) |
| Maintainer | Matt P. Wand <matt.wand@uts.edu.au> |
| License | GPL (>= 2) |
| Version | 1.0-2.2 |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
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