bspcov: Bayesian Sparse Estimation of a Covariance Matrix

Bayesian estimations of a covariance matrix for multivariate normal data. Assumes that the covariance matrix is sparse or band matrix and positive-definite. Methods implemented include the beta-mixture shrinkage prior (Lee et al. (2022) <doi:10.1016/j.jmva.2022.105067>), screened beta-mixture prior (Lee et al. (2024) <doi:10.1214/24-BA1495>), and post-processed posteriors for banded and sparse covariances (Lee et al. (2023) <doi:10.1214/22-BA1333>; Lee and Lee (2023) <doi:10.1016/j.jeconom.2023.105475>). This software has been developed using funding supported by Basic Science Research Program through the National Research Foundation of Korea ('NRF') funded by the Ministry of Education ('RS-2023-00211979', 'NRF-2022R1A5A7033499', 'NRF-2020R1A4A1018207' and 'NRF-2020R1C1C1A01013338').

Version:	1.0.2
Depends:	R (≥ 4.2)
Imports:	GIGrvg, coda, progress, BayesFactor, MASS, mvnfast, matrixcalc, matrixStats, purrr, dplyr, RSpectra, Matrix, plyr, CholWishart, magrittr, future, furrr, ks, ggplot2, ggmcmc, caret, FinCovRegularization, mvtnorm, stats
Suggests:	hdbinseg, POET, tidyquant, tidyr, timetk, quantmod
Published:	2025-07-02
DOI:	10.32614/CRAN.package.bspcov
Author:	Kwangmin Lee [aut], Kyeongwon Lee [aut, cre], Kyoungjae Lee [aut], Seongil Jo [aut], Jaeyong Lee [ctb]
Maintainer:	Kyeongwon Lee <kwlee1718 at gmail.com>
License:	GPL-2
URL:	https://github.com/statjs/bspcov
NeedsCompilation:	no
Materials:	README
CRAN checks:	bspcov results

Documentation:

Reference manual:

bspcov.pdf

Downloads:

Package source:	bspcov_1.0.2.tar.gz
Windows binaries:	r-devel: bspcov_1.0.2.zip, r-release: bspcov_1.0.2.zip, r-oldrel: bspcov_1.0.2.zip
macOS binaries:	r-release (arm64): bspcov_1.0.1.tgz, r-oldrel (arm64): bspcov_1.0.1.tgz, r-release (x86_64): bspcov_1.0.2.tgz, r-oldrel (x86_64): bspcov_1.0.2.tgz
Old sources:	bspcov archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=bspcov to link to this page.