Package: gilmour
Type: Package
Title: The Interpretation of Adjusted Cp Statistic
Version: 0.1.1
Authors@R: c(
    person(
      "Josef", "Dolejs",
      email = "josef.dolejs@uhk.cz",
      role = c("aut", "cre"),
      comment = c(ORCID = "0000-0002-3224-585X")
    )
  )
    #> [1] "Josef Dolejs <josef.dolejs@uhk.cz> [aut, cre] (ORCID <https//orcid.org/0000-0002-3224-585X>)"
VignetteBuilder: knitr
Suggests: knitr, rmarkdown
Description: Several methods may be found for selecting a subset of
        regressors from a set of k candidate variables in multiple
        linear regression. One possibility is to evaluate all possible
        regression models and comparing them using Mallows's Cp
        statistic (Cp) according to Gilmour original study. Full model
        is calculated, all possible combinations of regressors are
        generated, adjusted Cp for each submodel are computed, and the
        submodel with the minimum adjusted value Cp (ModelMin) is
        calculated. To identify the final model, the package applies a
        sequence of hypothesis tests on submodels nested within
        ModelMin, following the approach outlined in Gilmour's original
        paper. For more details see the help of the function
        final_model() and the original study (1996)
        <doi:10.2307/2348411>.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.3.2
Depends: R (>= 3.5)
NeedsCompilation: no
Packaged: 2026-06-18 06:27:49 UTC; root
Author: Josef Dolejs [aut, cre] (ORCID:
        <https://orcid.org/0000-0002-3224-585X>)
Maintainer: Josef Dolejs <josef.dolejs@uhk.cz>
Repository: https://dolejs1993.r-universe.dev
Date/Publication: 2025-07-10 13:50:02 UTC
RemoteUrl: https://github.com/cran/gilmour
RemoteRef: HEAD
RemoteSha: e951ac8c94d584577a0e920e4a9268a3a843d737