Package: mcemGLM 1.1.3

Felipe Acosta Archila

mcemGLM: Maximum Likelihood Estimation for Generalized Linear Mixed Models

Maximum likelihood estimation for generalized linear mixed models via Monte Carlo EM. For a description of the algorithm see Brian S. Caffo, Wolfgang Jank and Galin L. Jones (2005) <doi:10.1111/j.1467-9868.2005.00499.x>.

Authors:Felipe Acosta Archila

mcemGLM_1.1.3.tar.gz
mcemGLM_1.1.3.tar.gz(r-4.5-noble)mcemGLM_1.1.3.tar.gz(r-4.4-noble)
mcemGLM_1.1.3.tgz(r-4.4-emscripten)mcemGLM_1.1.3.tgz(r-4.3-emscripten)
mcemGLM.pdf |mcemGLM.html✨
mcemGLM/json (API)

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

Peer review:

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:

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

openblascpp

2.00 score 6 scripts 267 downloads 10 exports 3 dependencies

Last updated 2 years agofrom:dba031ed03. Checks:ERROR: 1 OK: 1. Indexed: no.

TargetResultDate
Doc / VignettesFAILDec 07 2024
R-4.5-linux-x86_64OKDec 07 2024

Exports:anova.mcemGLMMcoef.mcemGLMMcontrasts.mcemGLMMcovMat.mcemGLMMmcemGLMMmcemGLMMextpredict.mcemGLMMranef.mcemGLMMresiduals.mcemGLMMsummary.mcemGLMM

Dependencies:RcppRcppArmadillotrust

An R Package to Fit Generalized Linear Mixed Models

Rendered frommcemGLM-vignette.Rnwusingutils::Sweaveon Dec 07 2024.

Last update: 2020-03-03
Started: 2015-07-17