Package: GLMMselect 1.2.0
Shuangshuang Xu
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:
GLMMselect_1.2.0.tar.gz
GLMMselect_1.2.0.tar.gz(r-4.5-noble)GLMMselect_1.2.0.tar.gz(r-4.4-noble)
GLMMselect_1.2.0.tgz(r-4.4-emscripten)GLMMselect_1.2.0.tgz(r-4.3-emscripten)
GLMMselect.pdf |GLMMselect.html✨
GLMMselect/json (API)
NEWS
| # Install 'GLMMselect' in R: |
| install.packages('GLMMselect', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- 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
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 1 years agofrom:8e700a93b2. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Aug 19 2024 |
| R-4.5-linux | OK | Aug 19 2024 |
Exports:GLMMselect
Dependencies:
