PLStests: Model Checking for High-Dimensional GLMs via Random Projections

Provides methods for testing the goodness-of-fit of generalized linear models (GLMs) using random projections. It is specifically designed for high-dimensional scenarios where the number of predictors substantially exceeds the sample size. The statistical methodologies implemented in this package are detailed in the paper by Wen Chen and Falong Tan (2024, <doi:10.48550/arXiv.2412.10721>).

Version:	0.1.0
Depends:	R (≥ 3.5.0)
Imports:	glmnet, harmonicmeanp, MASS, psych, stats
Published:	2025-01-14
DOI:	10.32614/CRAN.package.PLStests
Author:	Wen Chen [aut, cre], Jie Liu [aut], Heng Peng [aut], FaLong Tan [aut], Lixing Zhu [aut]
Maintainer:	Wen Chen <tlqdcw at gmail.com>
License:	GPL-3
NeedsCompilation:	no
CRAN checks:	PLStests results

Documentation:

Reference manual:

PLStests.pdf

Downloads:

Package source:	PLStests_0.1.0.tar.gz
Windows binaries:	r-devel: not available, r-release: not available, r-oldrel: PLStests_0.1.0.zip
macOS binaries:	r-release (arm64): PLStests_0.1.0.tgz, r-oldrel (arm64): PLStests_0.1.0.tgz, r-release (x86_64): PLStests_0.1.0.tgz, r-oldrel (x86_64): PLStests_0.1.0.tgz

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