Package: picreg
Type: Package
Title: Variable Selection using the Pivotal Information Criterion
Version: 0.1.2
Date: 2026-05-30
Authors@R: c(
    person("Maxime", "van Cutsem",
           role  = c("aut", "cre"),
           email = "maxime.vancutsem@unige.ch"),
    person("Sylvain", "Sardy",
           role  = "aut",
           email = "sylvain.sardy@unige.ch"))
Description: Sparse regression and classification via the Pivotal
    Information Criterion (PIC), an alternative to the Bayesian
    Information Criterion (BIC), cross-validation, and Lasso-based
    tuning. The regularisation parameter is selected from a pivotal
    null-distribution statistic, eliminating the need for
    cross-validation and yielding sharper support recovery. Provides
    Fast Iterative Shrinkage-Thresholding Algorithm (FISTA)
    optimisation for the L1, Smoothly Clipped Absolute Deviation
    (SCAD), and Minimax Concave Penalty (MCP) penalties across six
    response distributions: Gaussian, binomial, Poisson, exponential,
    Gumbel, and Cox. Under standard sparsity assumptions, the
    selector achieves a phase transition for exact support recovery,
    analogous to results in compressed sensing. See Sardy, van Cutsem
    and van de Geer (2026) <doi:10.48550/arXiv.2603.04172>.
License: GPL-2
URL: https://github.com/VcMaxouuu/picreg
BugReports: https://github.com/VcMaxouuu/picreg/issues
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.6.0)
Imports: stats, graphics, grDevices, parallel, future, future.apply,
        Rcpp (>= 1.0.10)
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, xfun, glmnet
VignetteBuilder: knitr
SystemRequirements: C++17
RoxygenNote: 8.0.0
Config/roxygen2/version: 8.0.0
Config/testthat/edition: 3
NeedsCompilation: yes
Packaged: 2026-05-30 10:45:46 UTC; maxvancutsem
Author: Maxime van Cutsem [aut, cre],
  Sylvain Sardy [aut]
Maintainer: Maxime van Cutsem <maxime.vancutsem@unige.ch>
Repository: CRAN
Date/Publication: 2026-06-03 13:40:02 UTC
