Package: weightedScores 0.9.5.4

Aristidis K. Nikoloulopoulos

weightedScores: Weighted Scores Method for Regression Models with Dependent Data

The weighted scores method and composite likelihood information criteria as an intermediate step for variable/correlation selection for longitudinal ordinal and count data in Nikoloulopoulos, Joe and Chaganty (2011) <doi:10.1093/biostatistics/kxr005>, Nikoloulopoulos (2016) <doi:10.1002/sim.6871> and Nikoloulopoulos (2017) <doi:10.1080/00949655.2020.1759602>.

Authors:Aristidis K. Nikoloulopoulos [aut, cre], Harry Joe [aut]

weightedScores_0.9.5.4.tar.gz
weightedScores_0.9.5.4.zip(r-4.7-x86_64)weightedScores_0.9.5.4.zip(r-4.7-arm64)weightedScores_0.9.5.4.zip(r-4.6-x86_64)weightedScores_0.9.5.4.zip(r-4.6-arm64)
weightedScores_0.9.5.4.tar.gz(r-4.7-arm64)weightedScores_0.9.5.4.tar.gz(r-4.7-x86_64)weightedScores_0.9.5.4.tar.gz(r-4.6-arm64)weightedScores_0.9.5.4.tar.gz(r-4.6-x86_64)
weightedScores_0.9.5.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
weightedScores/json (API)

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

On CRAN:

Conda:

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

1.20 score 16 scripts 327 downloads 26 exports 2 dependencies

Last updated from:09de5990d5. Checks:10 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK122
linux-devel-x86_64OK140
source / vignettesOK166
linux-release-arm64OK164
linux-release-x86_64OK124
windows-devel-arm64OK248
windows-devel-x86_64OK138
windows-release-arm64OK207
windows-release-x86_64OK108
wasm-releaseOK107

Exports:approxbvncdfbclbcl.ordcl1cl1.ordclicclic1dePardmargmodeldmargmodel.ordgodambegodambe.ordieeiee.ordmvn.deriv.marginmvn.deriv.rhomvnapppmargmodelpmargmodel.ordscoreCovscoreCov.ordsolvewtscsolvewtsc.ordweightMatweightMat.ordwtsc.ord.wrapperwtsc.wrapper

Dependencies:mvtnormrootSolve