Package: bspcov
Type: Package
Title: Bayesian Sparse Estimation of a Covariance Matrix
Version: 1.0.3
Date: 2025-08-08
Maintainer: Kyeongwon Lee <kwlee1718@gmail.com>
Authors@R: c(person(given = "Kwangmin",
                  family = "Lee",
                  role = "aut"),
           person(given = "Kyeongwon",
                  family = "Lee",
                  role = c("aut", "cre"),
                  email = "kwlee1718@gmail.com"),
           person(given = "Kyoungjae",
                  family = "Lee",
                  role = "aut"),
           person(given = "Seongil",
                  family = "Jo",
                  role = "aut"),
           person(given = "Jaeyong",
                  family = "Lee",
                  role = "ctb"))
Author: Kwangmin Lee [aut], Kyeongwon Lee [aut, cre], Kyoungjae Lee
        [aut], Seongil Jo [aut], Jaeyong Lee [ctb]
Depends: R (>= 4.2)
Description: 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').
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, patchwork,
        reshape2, future.apply
Suggests: hdbinseg, POET, tidyquant, tidyr, timetk, quantmod
License: GPL-2
LazyLoad: yes
URL: https://github.com/statjs/bspcov
Encoding: UTF-8
RoxygenNote: 7.3.2
NeedsCompilation: no
Packaged: 2026-10-08 09:46:11 UTC; root
LazyData: true
LazyDataCompression: xz
Config/pak/sysreqs: libicu-dev libssl-dev pari-gp
Repository: https://statjs.r-universe.dev
Date/Publication: 2025-08-14 18:36:54 UTC
RemoteUrl: https://github.com/statjs/bspcov
RemoteRef: HEAD
RemoteSha: 4e199162d6df33b937bf4111a980f6457c6d6e46