Package: parglms 1.39.0

VJ Carey

parglms: support for parallelized estimation of GLMs/GEEs

This package provides support for parallelized estimation of GLMs/GEEs, catering for dispersed data.

Authors:VJ Carey <[email protected]>

parglms_1.39.0.tar.gz
parglms_1.39.0.zip(r-4.5)parglms_1.39.0.zip(r-4.4)parglms_1.39.0.zip(r-4.3)
parglms_1.39.0.tgz(r-4.4-any)parglms_1.39.0.tgz(r-4.3-any)
parglms_1.39.0.tar.gz(r-4.5-noble)parglms_1.39.0.tar.gz(r-4.4-noble)
parglms_1.39.0.tgz(r-4.4-emscripten)parglms_1.39.0.tgz(r-4.3-emscripten)
parglms.pdf |parglms.html
parglms/json (API)

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

Peer review:

On BioConductor:parglms-1.39.0(bioc 3.21)parglms-1.38.0(bioc 3.20)

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

3.30 score 3 scripts 240 downloads 1 exports 32 dependencies

Last updated 2 months agofrom:1e7c61f86e. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKDec 21 2024
R-4.5-winNOTEDec 21 2024
R-4.5-linuxNOTEDec 21 2024
R-4.4-winNOTEDec 21 2024
R-4.4-macNOTEDec 21 2024
R-4.3-winNOTEDec 21 2024
R-4.3-macNOTEDec 21 2024

Exports:parGLM

Dependencies:backportsbase64encBatchJobsBBmiscBiocGenericsbitbit64blobbrewcachemcheckmateclicodetoolscpp11data.tableDBIdigestdoParallelfastmapforeachgenericsglueiteratorslifecyclememoisepkgconfigplogrrlangRSQLitesendmailRstringivctrs

parglms: fitting generalized linear and related models with parallel evaluation of contributions to sufficient statistics

Rendered fromparglms.Rmdusingknitr::rmarkdownon Dec 21 2024.

Last update: 2020-10-26
Started: 2014-12-04

Readme and manuals

Help Manual

Help pageTopics
support for parallelized estimation of GLMs/GEEsparglms-package parglms
fit GLM-like models with parallelized contributions to sufficient statisticsparGLM parGLM,formula,Registry-method parGLM-methods predict predict.parglm print print.parglm summary summary.parglm