Package: PLStests 0.1.0

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>).

Authors:Wen Chen [aut, cre], Jie Liu [aut], Heng Peng [aut], FaLong Tan [aut], Lixing Zhu [aut]

PLStests_0.1.0.tar.gz
PLStests_0.1.0.zip(r-4.5)PLStests_0.1.0.zip(r-4.4)PLStests_0.1.0.zip(r-4.3)
PLStests_0.1.0.tgz(r-4.5-any)PLStests_0.1.0.tgz(r-4.4-any)PLStests_0.1.0.tgz(r-4.3-any)
PLStests_0.1.0.tar.gz(r-4.5-noble)PLStests_0.1.0.tar.gz(r-4.4-noble)
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PLStests.pdf |PLStests.html
PLStests/json (API)

# Install 'PLStests' in R:
install.packages('PLStests', repos = c('https://codingmylife.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:

On CRAN:

Conda-Forge:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 229 downloads 1 exports 17 dependencies

Last updated 2 months agofrom:1723bd864f. Checks:8 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 14 2025
R-4.5-winOKFeb 14 2025
R-4.5-macOKFeb 14 2025
R-4.5-linuxOKFeb 14 2025
R-4.4-winOKFeb 14 2025
R-4.4-macOKFeb 14 2025
R-4.3-winOKFeb 14 2025
R-4.3-macOKFeb 14 2025

Exports:PLStests

Dependencies:codetoolsFMStableforeachglmnetGPArotationharmonicmeanpiteratorslatticeMASSMatrixmnormtnlmepsychRcppRcppEigenshapesurvival