KDEmcmc: Kernel Density Estimation with a Markov Chain Monte Carlo Sample

Provides methods for selecting the optimal bandwidth in kernel density estimation for dependent samples, such as those generated by Markov chain Monte Carlo (MCMC). Implements a modified biased cross-validation (mBCV) approach that accounts for sample dependence, improving the accuracy of estimated density functions.

Version:	0.0.1
Depends:	R (≥ 3.5.0)
Imports:	Rcpp, methods
LinkingTo:	Rcpp, RcppArmadillo
Published:	2025-04-24
Author:	Juhee Lee [aut, cre], Hang J. Kim [aut], Young-Min Kim [aut]
Maintainer:	Juhee Lee <ljh988488 at gmail.com>
License:	GPL (≥ 3)
NeedsCompilation:	yes
CRAN checks:	KDEmcmc results

Documentation:

Reference manual:

KDEmcmc.pdf

Downloads:

Package source:	KDEmcmc_0.0.1.tar.gz
Windows binaries:	r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries:	r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): KDEmcmc_0.0.1.tgz, r-oldrel (x86_64): not available

Linking:

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