Package: spfcICOMP
Title: Shrinkage Principal Fitted Components with Information
        Complexity-Based Model Selection
Version: 0.1.0
Authors@R: 
    person("Kabir Opeyemi", "Olorede", email = "kabir.olorede@kwasu.edu.ng",
           role = c("aut", "cre", "cph"))
Description: Implements shrinkage principal fitted components for sufficient
    dimension reduction in high-dimensional regression and classification.
    Provides regularised covariance estimation using Oracle Approximating
    Shrinkage and Maximum Entropy Covariance, structural-dimension selection
    using conventional and information-complexity criteria, response-guided
    feature screening, reduced-space prediction, and simulation utilities.
    Methodological foundations include Cook and Forzani (2008)
    <doi:10.1214/08-STS275>, Chen et al. (2010)
    <doi:10.1109/TSP.2010.2053029>, Bozdogan (2000)
    <doi:10.1006/jmps.1999.1277>, and Olorede and Yahya (2019)
    <doi:10.48550/arXiv.1909.13017>.
License: MIT + file LICENSE
URL: https://github.com/ilovemaths/spfcICOMP
BugReports: https://github.com/ilovemaths/spfcICOMP/issues
Encoding: UTF-8
Language: en-GB
RoxygenNote: 7.3.3
Imports: MASS
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
Config/testthat/edition: 3
VignetteBuilder: knitr
Depends: R (>= 3.5.0)
NeedsCompilation: no
Packaged: 2026-08-21 20:26:55 UTC; DR OLOREDE
Author: Kabir Opeyemi Olorede [aut, cre, cph]
Maintainer: Kabir Opeyemi Olorede <kabir.olorede@kwasu.edu.ng>
Repository: CRAN
Date/Publication: 2026-09-03 13:50:02 UTC
Built: R 4.5.2; ; 2026-09-03 17:56:59 UTC; unix
