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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:0.0.2
Depends:R (≥ 3.5.0)
Imports:Rcpp, methods
LinkingTo:Rcpp,RcppArmadillo
Published:2025-08-19
DOI:10.32614/CRAN.package.KDEmcmc
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.html ,KDEmcmc.pdf

Downloads:

Package source: KDEmcmc_0.0.2.tar.gz
Windows binaries: r-devel:KDEmcmc_0.0.2.zip, r-release:KDEmcmc_0.0.2.zip, r-oldrel:KDEmcmc_0.0.2.zip
macOS binaries: r-release (arm64):KDEmcmc_0.0.2.tgz, r-oldrel (arm64):KDEmcmc_0.0.2.tgz, r-release (x86_64):KDEmcmc_0.0.2.tgz, r-oldrel (x86_64):KDEmcmc_0.0.2.tgz
Old sources: KDEmcmc archive

Linking:

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