ghcclm: Generalized Hybrid Contrast Coding in Linear Models

Implements generalized hybrid contrast coding methods for K-level categorical predictors in linear models as established by Obulezi (2026)[cite: 3]. The package automates design matrix construction mixing dummy indicators and composite group contrasts, checks rank constraints via singular value decomposition, computes closed-form OLS parameter mappings, and estimates robust heteroscedastic covariance matrices[cite: 3].

Version:	0.1.0
Depends:	R (≥ 4.0.0)
Imports:	stats
Suggests:	testthat (≥ 3.0.0)
Published:	2026-08-08
DOI:	10.32614/CRAN.package.ghcclm
Author:	Okechukwu J. Obulezi [aut, cre]
Maintainer:	Okechukwu J. Obulezi <oj.obulezi at unizik.edu.ng>
License:	MIT + file LICENSE
NeedsCompilation:	no
CRAN checks:	ghcclm results

Documentation:

Reference manual:

ghcclm.html , ghcclm.pdf

Downloads:

Package source:	ghcclm_0.1.0.tar.gz
Windows binaries:	r-devel: ghcclm_0.1.0.zip, r-release: ghcclm_0.1.0.zip, r-oldrel: ghcclm_0.1.0.zip
macOS binaries:	r-release (arm64): ghcclm_0.1.0.tgz, r-oldrel (arm64): ghcclm_0.1.0.tgz, r-release (x86_64): ghcclm_0.1.0.tgz, r-oldrel (x86_64): ghcclm_0.1.0.tgz

Linking:

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