Package: vglmer
Type: Package
Title: Variational Inference for Hierarchical Generalized Linear Models
Version: 1.0.3
Authors@R: person("Max", "Goplerud", email = "mgoplerud@pitt.edu", 
    role = c("aut", "cre"))
Encoding: UTF-8
License: GPL (>= 2)
Description: Estimates hierarchical models using mean-field variational Bayes. 
    At present, it can estimate logistic, linear, and negative binomial models. 
    It can accommodate models with an arbitrary number of random effects and 
    requires no integration to estimate. It also provides the ability to improve 
    the quality of the approximation using marginal augmentation. 
    Goplerud (2022) <doi:10.1214/21-BA1266> provides details on the variational
    algorithms.
Imports: Rcpp (>= 1.0.1), lme4, CholWishart, mvtnorm, Matrix, stats,
        graphics, methods, lmtest, splines, mgcv
Depends: R (>= 3.0.2)
Suggests: SuperLearner, MASS, tictoc, testthat
LinkingTo: Rcpp, RcppEigen (>= 0.3.3.4.0)
RoxygenNote: 7.2.1
URL: https://github.com/mgoplerud/vglmer
BugReports: https://github.com/mgoplerud/vglmer/issues
NeedsCompilation: yes
Packaged: 2022-10-27 17:41:46 UTC; MHG23
Author: Max Goplerud [aut, cre]
Maintainer: Max Goplerud <mgoplerud@pitt.edu>
Repository: CRAN
Date/Publication: 2022-10-27 22:00:02 UTC
Built: R 4.4.0; aarch64-apple-darwin20; 2024-04-07 04:41:18 UTC; unix
Archs: vglmer.so.dSYM
