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CRAN: Package bspcov

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

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