rpql

Regularized PQL for Joint Selection in GLMMs

Performs joint selection in Generalized Linear Mixed Models (GLMMs) using penalized likelihood methods. Specifically, the Penalized Quasi-Likelihood (PQL) is used as a loss function, and penalties are then augmented to perform simultaneous fixed and random effects selection. Regularized PQL avoids the need for integration (or approximations such as the Laplace's method) during the estimation process, and so the full solution path for model selection can be constructed relatively quickly.

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Description file content

Package
rpql
Title
Regularized PQL for Joint Selection in GLMMs
Version
0.7
Date
2018-12-20
Author
Francis K.C. Hui , with contributions from Samuel Mueller and A.H. Welsh
Maintainer
Francis Hui
Description
Performs joint selection in Generalized Linear Mixed Models (GLMMs) using penalized likelihood methods. Specifically, the Penalized Quasi-Likelihood (PQL) is used as a loss function, and penalties are then augmented to perform simultaneous fixed and random effects selection. Regularized PQL avoids the need for integration (or approximations such as the Laplace's method) during the estimation process, and so the full solution path for model selection can be constructed relatively quickly.
License
GPL-2
Imports
gamlss.dist, lme4, Matrix, MASS, mvtnorm, Rcpp,
Suggests
nlme
NeedsCompilation
yes
LinkingTo
Rcpp, RcppArmadillo
Packaged
2018-12-05 21:42:48 UTC; francis
Repository
CRAN
Date/Publication
2018-12-05 22:00:03 UTC

install.packages('rpql')

0.7

4 days ago

Francis Hui

GPL-2

Imports

gamlss.dist, lme4, Matrix, MASS, mvtnorm, Rcpp,

Suggests

nlme

Discussions