Package: densEstBayes 1.0-2.2

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>.

Authors:Matt P. Wand [aut, cre]

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densEstBayes/json (API)

# Install 'densEstBayes' in R:
install.packages('densEstBayes', repos = c('https://mattwand.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

3.72 score 8 packages 15 scripts 1.5k downloads 6 exports 54 dependencies

Last updated 2 years agofrom:fe67eca347. Checks:OK: 2 NOTE: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 26 2024
R-4.5-win-x86_64NOTEOct 26 2024
R-4.5-linux-x86_64OKOct 26 2024
R-4.4-win-x86_64NOTEOct 26 2024
R-4.4-mac-x86_64NOTEOct 26 2024
R-4.4-mac-aarch64NOTEOct 26 2024
R-4.3-win-x86_64NOTEOct 26 2024
R-4.3-mac-x86_64NOTEOct 26 2024
R-4.3-mac-aarch64NOTEOct 26 2024

Exports:checkChainsdensEstBayesdensEstBayes.controldensEstBayesVignettedMarronWandrMarronWand

Dependencies:abindbackportsBHcallrcheckmateclicolorspacedescdistributionalfansifarvergenericsggplot2gluegridExtragtableinlineisobandlabelinglatticelifecycleloomagrittrMASSMatrixmatrixStatsmgcvmunsellnlmenumDerivpillarpkgbuildpkgconfigposteriorprocessxpsQuickJSRR6RColorBrewerRcppRcppArmadilloRcppEigenRcppParallelrlangrstanrstantoolsscalesStanHeaderstensorAtibbleutf8vctrsviridisLitewithr

densEstBayes User Manual

Rendered frommanual.Rnwusingutils::Sweaveon Oct 26 2024.

Last update: 2020-09-30
Started: 2020-09-30