Package: bspcov
Type: Package
Title: Bayesian Sparse Estimation of a Covariance Matrix
Version: 1.0.3
Date: 2025-08-14
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: 2025-08-14 02:52:08 UTC; runner
LazyData: true
LazyDataCompression: xz
Repository: CRAN
Date/Publication: 2025-08-18 19:20:30 UTC
Built: R 4.6.0; ; 2025-10-14 03:51:12 UTC; windows
