Package: GLMMselect 1.2.0

GLMMselect: Bayesian Model Selection for Generalized Linear Mixed Models

A Bayesian model selection approach for generalized linear mixed models. Currently, 'GLMMselect' can be used for Poisson GLMM and Bernoulli GLMM. 'GLMMselect' can select fixed effects and random effects simultaneously. Covariance structures for the random effects are a product of a unknown scalar and a known semi-positive definite matrix. 'GLMMselect' can be widely used in areas such as longitudinal studies, genome-wide association studies, and spatial statistics. 'GLMMselect' is based on Xu, Ferreira, Porter, and Franck (202X), Bayesian Model Selection Method for Generalized Linear Mixed Models, Biometrics, under review.

Authors:Shuangshuang Xu [aut, cre], Marco Ferreira [aut], Erica Porter [aut], Christopher Franck [aut]

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GLMMselect.pdf |GLMMselect.html
GLMMselect/json (API)
NEWS

# Install 'GLMMselect' in R:
install.packages('GLMMselect', repos = c('https://xss55.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • Sigma - A list of covariance matrices
  • X - The matrix of candidate covariates
  • Y - The vector of observations
  • Z - A list of design matrices
  • lipcancer_Sigma - A list of covariance matrices
  • lipcancer_X - The matrix of candidate covariates
  • lipcancer_Y - The vector of observations for lip cancer case study
  • lipcancer_Z - A list of design matrices
  • lipcancer_offset - The vector of priori information for lip cancer case study

On CRAN:

Conda:

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

2.70 score 9 scripts 191 downloads 1 exports 0 dependencies

Last updated 2 years agofrom:8e700a93b2. Checks:9 OK. Indexed: yes.

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Doc / VignettesOKMar 14 2025
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R-4.4-macOKMar 14 2025
R-4.4-linuxOKMar 14 2025
R-4.3-winOKMar 14 2025
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GLMMselect: Bayesian model selection for generalized linear mixed models

Rendered fromGLMMselect_vignette.Rmdusingknitr::rmarkdownon Mar 14 2025.

Last update: 2023-04-20
Started: 2023-04-20