Package: smoothic
Type: Package
Title: Variable Selection Using a Smooth Information Criterion
Version: 1.2.1
Depends: R (>= 3.5.0)
Authors@R: c(person("Meadhbh", "O'Neill", email = "meadhbhon@gmail.com", role = c("aut", "cre")), person("Kevin", "Burke", role = c("aut")))
Maintainer: Meadhbh O'Neill <meadhbhon@gmail.com>
Description: Implementation of the SIC epsilon-telescope method, either
        using single or distributional (multiparameter) regression.
        Includes classical regression with normally distributed errors
        and robust regression, where the errors are from the Laplace
        distribution. The "smooth generalized normal distribution" is
        used, where the estimation of an additional shape parameter
        allows the user to move smoothly between both types of
        regression. See O'Neill and Burke (2022) "Robust Distributional
        Regression with Automatic Variable Selection" for more details.
        <doi:10.48550/arXiv.2212.07317>. This package also contains the
        data analyses from O'Neill and Burke (2023). "Variable
        selection using a smooth information criterion for
        distributional regression models".
        <doi:10.1007/s11222-023-10204-8>.
License: GPL-3
URL: https://meadhbh-oneill.github.io/smoothic/,
        https://github.com/meadhbh-oneill/smoothic
BugReports: https://github.com/meadhbh-oneill/smoothic/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.3.3
Imports: data.table, dplyr, ggplot2, MASS, numDeriv, purrr, rlang,
        stringr, tibble, tidyr, toOrdinal
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
Config/pak/sysreqs: libicu-dev libssl-dev
Repository: https://meadhbh-oneill.r-universe.dev
Date/Publication: 2025-09-16 20:02:54 UTC
RemoteUrl: https://github.com/meadhbh-oneill/smoothic
RemoteRef: HEAD
RemoteSha: 4e35b1d8dd1e4bdff91191f9641f58300b30b56a
NeedsCompilation: no
Packaged: 2026-07-13 07:56:17 UTC; root
Author: Meadhbh O'Neill [aut, cre],
  Kevin Burke [aut]