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
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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'))

Peer review:

Datasets:

On CRAN:

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

1.00 score 1 exports 17 dependencies

Last updated 8 days agofrom:1723bd864f. Checks:7 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKJan 15 2025
R-4.5-winOKJan 15 2025
R-4.5-linuxOKJan 15 2025
R-4.4-winOKJan 15 2025
R-4.4-macOKJan 15 2025
R-4.3-winOKJan 15 2025
R-4.3-macOKJan 15 2025

Exports:PLStests

Dependencies:codetoolsFMStableforeachglmnetGPArotationharmonicmeanpiteratorslatticeMASSMatrixmnormtnlmepsychRcppRcppEigenshapesurvival