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 |