Learn R Programming

densEstBayes (version 1.0-2.2)

Density Estimation via Bayesian Inference Engines

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) .

Copy Link

Version

Install

install.packages('densEstBayes')

Monthly Downloads

1,823

Version

1.0-2.2

License

GPL (>= 2)

Maintainer

Matt Wand

Last Published

March 31st, 2023

Functions in densEstBayes (1.0-2.2)

densEstBayes

Density estimation via Bayesian inference engines
dMarronWand

Marron and Wand density function
predict.densEstBayes

Obtain the Bayesian density estimate from a densEstBayes() fit at new abscissae
checkChains

Check Markov chain Monte Carlo samples
densEstBayesVignette

Display the package's vignette.
densEstBayes.control

Controlling density estimation via Bayesian inference engines
OldFaithful2011

Intervals between geyser eruptions
rMarronWand

Marron and Wand random sample
incomeUK

Incomes of United Kingdom citizens
plot.densEstBayes

Plot the Bayesian density estimate from a densEstBayes() fit