spfcICOMP: Shrinkage Principal Fitted Components with Information Complexity-Based Model Selection

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>.

Version:	0.1.0
Depends:	R (≥ 3.5.0)
Imports:	MASS
Suggests:	testthat (≥ 3.0.0), knitr, rmarkdown
Published:	2026-09-03
DOI:	10.32614/CRAN.package.spfcICOMP
Author:	Kabir Opeyemi Olorede [aut, cre, cph]
Maintainer:	Kabir Opeyemi Olorede <kabir.olorede at kwasu.edu.ng>
BugReports:	https://github.com/ilovemaths/spfcICOMP/issues
License:	MIT + file LICENSE
URL:	https://github.com/ilovemaths/spfcICOMP
NeedsCompilation:	no
Language:	en-GB
Citation:	spfcICOMP citation info
Materials:	README, NEWS
CRAN checks:	spfcICOMP results

Documentation:

Reference manual:	spfcICOMP.html , spfcICOMP.pdf
Vignettes:	Getting Started with spfcICOMP (source, R code)

Downloads:

Package source:	spfcICOMP_0.1.0.tar.gz
Windows binaries:	r-devel: spfcICOMP_0.1.0.zip, r-release: spfcICOMP_0.1.0.zip, r-oldrel: spfcICOMP_0.1.0.zip
macOS binaries:	r-release (arm64): spfcICOMP_0.1.0.tgz, r-oldrel (arm64): spfcICOMP_0.1.0.tgz, r-release (x86_64): spfcICOMP_0.1.0.tgz, r-oldrel (x86_64): spfcICOMP_0.1.0.tgz

Linking:

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