bspcov: Bayesian Sparse Estimation of a Covariance Matrix

Provides functions which perform Bayesian estimations of a covariance matrix for multivariate normal data. Assumes that the covariance matrix is sparse or band matrix and positive-definite. 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: 1.0.0
Depends: R (≥ 3.5)
Imports: GIGrvg, coda, progress, BayesFactor, MASS, mvnfast, matrixcalc, matrixStats, purrr, dplyr, RSpectra, Matrix, plyr, CholWishart, magrittr, future, furrr, ks, ggplot2, ggmcmc, caret, FinCovRegularization, mvtnorm
Published: 2024-02-06
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_1.0.0.tar.gz
Windows binaries: r-devel: bspcov_1.0.0.zip, r-release: bspcov_1.0.0.zip, r-oldrel: bspcov_1.0.0.zip
macOS binaries: r-release (arm64): bspcov_1.0.0.tgz, r-oldrel (arm64): bspcov_1.0.0.tgz, r-release (x86_64): bspcov_1.0.0.tgz

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