Package: hglm 2.2-1

Xia Shen

hglm: Hierarchical Generalized Linear Models

Implemented here are procedures for fitting hierarchical generalized linear models (HGLM). It can be used for linear mixed models and generalized linear mixed models with random effects for a variety of links and a variety of distributions for both the outcomes and the random effects. Fixed effects can also be fitted in the dispersion part of the mean model. As statistical models, HGLMs were initially developed by Lee and Nelder (1996) <https://www.jstor.org/stable/2346105?seq=1>. We provide an implementation (Ronnegard, Alam and Shen 2010) <https://journal.r-project.org/archive/2010-2/RJournal_2010-2_Roennegaard~et~al.pdf> following Lee, Nelder and Pawitan (2006) <ISBN: 9781420011340> with algorithms extended for spatial modeling (Alam, Ronnegard and Shen 2015) <https://journal.r-project.org/archive/2015/RJ-2015-017/RJ-2015-017.pdf>.

Authors:Moudud Alam, Lars Ronnegard, Xia Shen

hglm_2.2-1.tar.gz
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hglm.pdf |hglm.html✨
hglm/json (API)

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

Peer review:

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

3.30 score 2 stars 78 scripts 481 downloads 21 mentions 8 exports 5 dependencies

Last updated 6 years agofrom:59125b70c7. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKDec 12 2024
R-4.5-linuxOKDec 12 2024

Exports:BetaCARhglmhglm2inverse.gammainverse.sqrtlrtSAR

Dependencies:hglm.datalatticeMASSMatrixsp

The hglm Package

Rendered fromhglm.Rnwusingutils::Sweaveon Dec 12 2024.

Last update: 2018-08-31
Started: 2014-01-01