Package: oscar
Type: Package
Title: Optimal Subset Cardinality Regression (OSCAR) Models Using the
        L0-Pseudonorm
Version: 1.2.1
Date: 2023-10-02
Authors@R: c(
    person(given=c("Teemu", "Daniel"), family="Laajala", role=c("aut", "cre"), email="teelaa@utu.fi", comment = c(ORCID = "0000-0002-7016-7354")),
    person(given="Kaisa", family="Joki", role=c("aut"), email="kjjoki@utu.fi"),
    person(given="Anni", family="Halkola", role=c("aut"), email="ansuha@utu.fi"))
Description: Optimal Subset Cardinality Regression (OSCAR) models offer
        regularized linear regression using the L0-pseudonorm,
        conventionally known as the number of non-zero coefficients.
        The package estimates an optimal subset of features using the
        L0-penalization via cross-validation, bootstrapping and visual
        diagnostics. Effective Fortran implementations are offered
        along the package for finding optima for the DC-decomposition,
        which is used for transforming the discrete L0-regularized
        optimization problem into a continuous non-convex optimization
        task. These optimization modules include DBDC ('Double Bundle
        method for nonsmooth DC optimization' as described in Joki et
        al. (2018) <doi:10.1137/16M1115733>) and LMBM ('Limited Memory
        Bundle Method for large-scale nonsmooth optimization' as in
        Haarala et al. (2004) <doi:10.1080/10556780410001689225>). The
        OSCAR models are comprehensively exemplified in Halkola et al.
        (2023) <doi:10.1371/journal.pcbi.1010333>). Multiple regression
        model families are supported: Cox, logistic, and Gaussian.
License: GPL-3
LazyData: true
URL: https://github.com/Syksy/oscar
BugReports: https://github.com/Syksy/oscar/issues
NeedsCompilation: yes
Depends: R (>= 4.1.0)
Imports: graphics, grDevices, hamlet, Matrix, methods, stats, survival,
        utils, pROC
Suggests: ePCR, glmnet, knitr, rmarkdown
VignetteBuilder: knitr
Encoding: UTF-8
RoxygenNote: 7.2.3
Packaged: 2026-10-07 13:05:05 UTC; root
Author: Teemu Daniel Laajala [aut, cre]
        (<https://orcid.org/0000-0002-7016-7354>), Kaisa Joki [aut],
        Anni Halkola [aut]
Maintainer: Teemu Daniel Laajala <teelaa@utu.fi>
Repository: https://cran.r-universe.dev
Date/Publication: 2023-10-02 15:31:15 UTC
RemoteUrl: https://github.com/cran/oscar
RemoteRef: HEAD
RemoteSha: 86316f02b44ee45c7c072388fe840c2ea599b518