Package: VsusP
Title: Variable Selection Using Shrinkage Priors
Version: 1.1.0
Authors@R: c(
            person("Nilson", "Chapagain", email = "nilson.chapagain@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-2962-2949")),
            person("Debdeep", "Pati", email = "debdeep@tamu.edu", role = c("aut"))
            )
Description: Select variables from shrinkage-prior posterior coefficient draws
    using sequential two-means clustering from Li and Pati (2017)
    <doi:10.1016/j.csda.2016.10.008>. Estimate a signal count at each tuning
    threshold and rank coefficients by posterior median absolute magnitude.
    Accept supplied coefficient draws or fit Gaussian shrinkage regression
    through 'bayesreg' or native ridge, horseshoe and spike-and-slab samplers.
    Retain chain identities for diagnostics, prediction and posterior plots.
    Also provide the signal adaptive variable selector
    of Ray and Bhattacharya (2018) <doi:10.48550/arXiv.1810.09004>,
    decoupled shrinkage and selection with the adaptive-L1 approximation of
    Hahn and Carvalho (2015) <doi:10.1080/01621459.2014.993077>, optional
    exact two-cluster fitting, basic two-means selection, exact-zero
    spike-and-slab inclusion summaries and tuning sensitivity summaries.
License: GPL (>= 3)
Encoding: UTF-8
RoxygenNote: 7.3.3
Imports: bayesreg, graphics, stats, utils
Suggests: posterior (>= 1.6.0), covr, MASS, knitr, rmarkdown, tinytex,
        testthat (>= 3.2.0)
Config/testthat/edition: 3
Maintainer: Nilson Chapagain <nilson.chapagain@gmail.com>
URL:
        https://github.com/nilson01/VsusP-variable-selection-using-shrinkage-priors
BugReports: https://github.com/nilson01/VsusP-variable-selection-using-shrinkage-priors/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-28 15:34:37 UTC; nilson
Author: Nilson Chapagain [aut, cre] (ORCID:
    <https://orcid.org/0000-0003-2962-2949>),
  Debdeep Pati [aut]
Repository: CRAN
Date/Publication: 2026-10-28 17:00:02 UTC
Built: R 4.7.0; ; 2026-10-29 11:30:18 UTC; windows
