Package: rpql 0.8.3

rpql: Regularized PQL for Joint Selection in GLMMs

Performs joint selection in Generalized Linear Mixed Models (GLMMs) using penalized likelihood methods. Specifically, the Penalized Quasi-Likelihood (PQL) is used as a loss function, and penalties are then augmented to perform simultaneous fixed and random effects selection. Regularized PQL avoids the need for integration (or approximations such as the Laplace's method) during the estimation process, and so the full solution path for model selection can be constructed relatively quickly.

Authors:Francis K.C. Hui [aut, cre]

rpql_0.8.3.tar.gz
rpql_0.8.3.zip(r-4.7)rpql_0.8.3.zip(r-4.6)rpql_0.8.3.zip(r-4.5)
rpql_0.8.3.tgz(r-4.6-x86_64)rpql_0.8.3.tgz(r-4.6-arm64)rpql_0.8.3.tgz(r-4.5-x86_64)rpql_0.8.3.tgz(r-4.5-arm64)
rpql_0.8.3.tar.gz(r-4.7-arm64)rpql_0.8.3.tar.gz(r-4.7-x86_64)rpql_0.8.3.tar.gz(r-4.6-arm64)rpql_0.8.3.tar.gz(r-4.6-x86_64)
rpql_0.8.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
rpql/json (API)

# Install 'rpql' in R:
install.packages('rpql', repos = c('https://fhui28.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

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

openblascpp

1.56 score 18 scripts 206 downloads 9 exports 17 dependencies

Last updated from:c3ee81f749. Checks:12 OK, 1 FAIL. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK129
linux-devel-x86_64OK197
source / vignettesOK182
linux-release-arm64OK131
linux-release-x86_64OK135
macos-release-arm64OK189
macos-release-x86_64OK263
macos-oldrel-arm64OK193
macos-oldrel-x86_64OK418
windows-develOK144
windows-releaseOK124
windows-oldrelOK126
wasm-releaseFAIL1427

Exports:build.start.fitcalc.marglogLgendat.glmmlseqnb2rpqlrpql.defaultrpqlseqsummary.rpql

Dependencies:bootgamlss.distlatticelme4MASSMatrixminqamvtnormnlmenloptrrbibutilsRcppRcppArmadilloRcppEigenRdpackreformulasrlang