Shrinkage Principal Fitted Components with Information Complexity-Based Model Selection
Overview
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.
- Began GitHub and CRAN release hardening without changing the statistical methodology or thesis-result implementation.
- Added repository metadata, README, citation metadata, and CRAN-preparation notes.
- Excluded thesis-analysis artefacts and exploratory outputs from the CRAN source tarball while retaining them for GitHub reproducibility.
- Replaced over-strong public wording about sparsity/selection with feature-screening terminology where appropriate.
- Removed third-party Riboflavin and Golub benchmark copies from the distributable package; the GitHub thesis-analysis layer now obtains Riboflavin from the archived CRAN
hdi0.1-10 source (with an installed-hdifast path when available) and Golub from Bioconductormulttestwhen empirical reproduction is requested. - Passed a local CRAN-style check with 0 errors, 0 warnings, and 0 notes and established a five-platform GitHub Actions R CMD check workflow.
- Hardened validation stratification so numeric binary responses are treated as categorical strata in train-test splitting and cross-validation fold construction.
- Added regression tests for numeric binary-response stratification without changing the statistical methodology or thesis-result implementation.
- Verified 149/149 local tests, a local R CMD check with 0 errors, 0 warnings, and 0 notes, exact R 3.5.0 compatibility, and the five-platform GitHub Actions matrix at commit fc80e696b7a64a2b8ab7c274f0af6c13e0fbb8ff.
- Made citation metadata safe to evaluate before package installation by removing the runtime package-description lookup.
- Declared British English and added a reviewed spelling wordlist for technical terms, acronyms, proper names, and method identifiers.
- Built and verified the exact 0.1.0 source tarball with 149/149 test expectations passing, no spelling flags, no missing or forbidden source-package entries, and a Windows R 4.6.0 R CMD check result of 0 errors, 0 warnings, and 0 notes.
From NEWS.md in the release
Install
Health
- OK13 OKNow
- OK6 OK2026-09-04
Documentation
- Help pages
- 52
- Examples that run
- 81%29 run in a plain check · 7 only when donttest examples are enabled (R CMD check --as-cran)
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 0%
Downloads
Repository
Releases over time
Commits over time
Commit identities over time
5 development-tooling and community-health practices detected across 4 families in the upstream repository
Checks run against github.com/ilovemaths/spfcicomp on 2026-10-21.
The R CMD check workflow runs on Linux, macOS and Windows, and on R-devel
Dependencies
Installing spfcICOMP adds no packages beyond those that come with R.
Code & Tests
People & History
- 0.1.0Latest2026-09-03 · current release
- RR 4.6.0 released · 2026-04-24
Package metadata
- First published
- 2026-09-03
- Total releases
- 1 / 1 yrs
- License
- MIT + file LICENSE OSI
- Minimum R
- ≥ 3.5.0
- Download size
- 78 KB
Cite
Cite this package
Run in R for the authors' entry:
citation("spfcICOMP")The package provides a citation file, so citation() returns the authors' own entry.
The repository also keeps a CITATION.cff.
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From data release v2026-10-25, which the citation names so these numbers can be found later. More on citing and the projects behind them.