Package: dhglm 2.0

dhglm: Double Hierarchical Generalized Linear Models

Implements double hierarchical generalized linear models in which the mean, dispersion parameters for variance of random effects, and residual variance (overdispersion) can be further modeled as random-effect models.

Authors:Youngjo Lee, Maengseok Noh

dhglm_2.0.tar.gz
dhglm_2.0.zip(r-4.7)dhglm_2.0.zip(r-4.6)dhglm_2.0.zip(r-4.5)
dhglm_2.0.tgz(r-4.6-any)dhglm_2.0.tgz(r-4.5-any)
dhglm_2.0.tar.gz(r-4.7-any)dhglm_2.0.tar.gz(r-4.6-any)
dhglm_2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
dhglm/json (API)

# Install 'dhglm' in R:
install.packages('dhglm', repos = c('https://msnoh1.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.

1.00 score 1 stars 7 scripts 305 downloads 3 exports 70 dependencies

Last updated from:a83ad49e70. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK171
source / vignettesOK206
linux-release-x86_64OK194
macos-release-arm64OK166
macos-oldrel-arm64OK97
windows-develOK130
windows-releaseOK127
windows-oldrelOK121
wasm-releaseOK104

Exports:dhglmfitDHGLMMODELINGplotdhglm

Dependencies:abindbackportsbootbroomcarcarDataclicolorspacecowplotcpp11DerivdoBydplyrfarverforecastFormulafracdiffgenericsggplot2gluegtableisobandlabelinglatticelifecyclelme4lmtestmagrittrMASSMatrixMatrixModelsmgcvmicrobenchmarkminqamodelrnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigpurrrquantregR6rbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreformulasrlangS7sandwichscalesSparseMstringistringrsurvivaltibbletidyrtidyselecttimeDateurcautf8vctrsviridisLitewithrzoo