Package: McMiso
Type: Package
Title: Multicore Multivariable Isotonic Regression
Version: 0.2.0
Authors@R: person("Cheung", "Ken", email = "yc632@cumc.columbia.edu",
    role = c("aut", "cre"))
Description: Provides functions for isotonic regression and classification
    when there are multiple independent variables. The functions solve the
    optimization problem using a projective Bayes approach with recursive
    sequential update algorithms, and are useful for situations with a
    relatively large number of covariates. Supports binary outcomes via a
    Beta-Binomial conjugate model ('miso', 'PBclassifier') and continuous
    outcomes via a Normal-Inverse-Chi-Squared conjugate model ('misoN').
    Parallel computing wrappers ('mcmiso', 'mcPBclassifier', 'mcmisoN') are
    provided that run the down-up and up-down algorithms simultaneously and
    return whichever finishes first. The estimation method follows the
    projective Bayes solution described in Cheung and Diaz (2023)
    <doi:10.1093/jrsssb/qkad014>.
Depends: R (>= 4.0.0)
Imports: stats, utils
Suggests: future (>= 1.33.0)
License: GPL-3
Encoding: UTF-8
RoxygenNote: 7.3.2
NeedsCompilation: no
Packaged: 2026-04-03 17:21:04 UTC; yingkuencheung
Author: Cheung Ken [aut, cre]
Maintainer: Cheung Ken <yc632@cumc.columbia.edu>
Repository: CRAN
Date/Publication: 2026-04-03 17:40:02 UTC
Built: R 4.6.0; ; 2026-04-25 20:15:30 UTC; unix
