Package: glmm 1.4.5

Christina Knudson

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.tar.gz(r-4.5-noble)glmm_1.4.5.tar.gz(r-4.4-noble)
glmm_1.4.5.tgz(r-4.4-emscripten)glmm_1.4.5.tgz(r-4.3-emscripten)
glmm.pdf |glmm.html
glmm/json (API)

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

Peer review:

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

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

4.65 score 2 stars 215 scripts 1.0k downloads 32 mentions 12 exports 9 dependencies

Last updated 3 months agofrom:ebacdba823. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKNov 22 2024
R-4.5-linux-x86_64OKNov 22 2024

Exports:bernoulli.glmmbinomial.glmmcoef.glmmglmmlogLik.glmmmcsemcvcovpoisson.glmmsesummary.glmmvarcompsvcov.glmm

Dependencies:codetoolsdoParallelforeachiteratorsitertoolslatticeMatrixmvtnormtrust

author2019mypaper

Rendered fromvignettes.Rnwusingutils::Sweaveon Nov 22 2024.

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