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GLMMselect  

Bayesian Model Selection for Generalized Linear Mixed Models
View on CRAN: Click here


Download and install GLMMselect package within the R console
Install from CRAN:
install.packages("GLMMselect")

Install from Github:
library("remotes")
install_github("cran/GLMMselect")

Install by package version:
library("remotes")
install_version("GLMMselect", "1.2.0")



Attach the package and use:
library("GLMMselect")
Maintained by
Shuangshuang Xu
[Scholar Profile | Author Map]
First Published: 2023-04-20
Latest Update: 2023-08-24
Description:
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.
How to cite:
Shuangshuang Xu (2023). GLMMselect: Bayesian Model Selection for Generalized Linear Mixed Models. R package version 1.2.0, https://cran.r-project.org/web/packages/GLMMselect. Accessed 17 Feb. 2025.
Previous versions and publish date:
1.0.0 (2023-04-20 10:20), 1.1.0 (2023-08-23 23:30)
Other packages that cited GLMMselect R package
View GLMMselect citation profile
Other R packages that GLMMselect depends, imports, suggests or enhances
Complete documentation for GLMMselect
Functions, R codes and Examples using the GLMMselect R package
Full GLMMselect package functions and examples
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