Package: glmm 1.4.5

glmm: Generalized Linear Mixed Models via Monte Carlo Likelihood Approximation

Approximates the likelihood of a generalized linear mixed model using Monte Carlo likelihood approximation. Then maximizes the likelihood approximation to return maximum likelihood estimates, observed Fisher information, and other model information.

Authors:Christina Knudson [aut, cre], Charles J. Geyer [ctb], Sydney Benson [ctb]

glmm_1.4.5.tar.gz
glmm_1.4.5.zip(r-4.7)glmm_1.4.5.zip(r-4.6)glmm_1.4.5.zip(r-4.5)
glmm_1.4.5.tgz(r-4.6-x86_64)glmm_1.4.5.tgz(r-4.6-arm64)glmm_1.4.5.tgz(r-4.5-x86_64)glmm_1.4.5.tgz(r-4.5-arm64)
glmm_1.4.5.tar.gz(r-4.7-arm64)glmm_1.4.5.tar.gz(r-4.7-x86_64)glmm_1.4.5.tar.gz(r-4.6-arm64)glmm_1.4.5.tar.gz(r-4.6-x86_64)
glmm_1.4.5.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
glmm/json (API)

# Install 'glmm' in R:

install.packages('glmm', repos = c('https://knudson1.r-universe.dev', 'https://cloud.r-project.org'))

Uses libs:

openblas– Optimized BLAS

Datasets:

bacteria - Presence of Bacteria after Drug Treatments
Booth2 - A Logit-Normal GLMM Dataset
BoothHobert - A Logit-Normal GLMM Dataset from Booth and Hobert
cbpp2 - Contagious Bovine Pleuropneumonia
murder - Number of Homicide Victims Known
radish2 - Radish count data set
salamander - Salamander mating data set from McCullagh and Nelder

On CRAN:

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

openblas

4.72 score 2 stars 265 scripts 595 downloads 32 mentions 12 exports 9 dependencies

Last updated from:ebacdba823. Checks:13 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	OK	243
linux-devel-x86_64	OK	196
source / vignettes	OK	173
linux-release-arm64	OK	200
linux-release-x86_64	OK	209
macos-release-arm64	OK	124
macos-release-x86_64	OK	406
macos-oldrel-arm64	OK	197
macos-oldrel-x86_64	OK	363
windows-devel	OK	158
windows-release	OK	151
windows-oldrel	OK	137
wasm-release	OK	100

Exports:bernoulli.glmm binomial.glmm coef.glmm glmm logLik.glmm mcse mcvcov poisson.glmm se summary.glmm varcomps vcov.glmm

Dependencies:codetools doParallel foreach iterators itertools lattice Matrix mvtnorm trust

author2019mypaper

Rendered fromvignettes.Rnwusingutils::Sweaveon May 08 2026.

Last update: 2022-04-07
Started: 2022-04-07

Citation

Readme and manuals

Help Manual

Help page	Topics
Presence of Bacteria after Drug Treatments	bacteria
Functions for the Bernoulli family.	bernoulli.glmm
Functions for the Binomial family.	binomial.glmm
A Logit-Normal GLMM Dataset	Booth2
A Logit-Normal GLMM Dataset from Booth and Hobert	BoothHobert
Contagious Bovine Pleuropneumonia	cbpp2
Extract Model Coefficients	coef.glmm
Calculates Asymptotic Confidence Intervals	confint.glmm
Fitting Generalized Linear Mixed Models using MCML	glmm
Monte Carlo Log Likelihood	logLik.glmm
Monte Carlo Standard Error	mcse
Monte Carlo Variance Covariance Matrix	mcvcov
Number of Homicide Victims Known	murder
Functions for the Poisson family.	poisson.glmm
Radish count data set	radish2
Salamander mating data set from McCullagh and Nelder (1989)	salamander
Standard Error	se
Summarizing GLMM Fits	print.summary.glmm summary.glmm
Extract Model Variance Components	varcomps
Variance-Covariance Matrix	vcov.glmm