Package: glmmsr
Title: Fit a Generalized Linear Mixed Model
Version: 0.2.2
Authors@R: person("Helen", "Ogden", , "heogden12@gmail.com", role = c("aut", "cre"))
Description: Conduct inference about generalized linear mixed models, with a
    choice about which method to use to approximate the likelihood. In addition
    to the Laplace and adaptive Gaussian quadrature approximations, which are
    borrowed from 'lme4', the likelihood may be approximated by the sequential
    reduction approximation, or an importance sampling approximation. These
    methods provide an accurate approximation to the likelihood in some
    situations where it is not possible to use adaptive Gaussian quadrature.
Depends: R (>= 3.2.0)
LinkingTo: Rcpp, RcppEigen, BH
Imports: lme4 (>= 1.1-8), Matrix, R6, Rcpp, methods, stats, utils,
        numDeriv
URL: http://github.com/heogden/glmmsr
BugReports: http://github.com/heogden/glmmsr/issues
License: GPL (>= 2)
LazyData: true
Suggests: BradleyTerry2, hglm.data, knitr, rmarkdown, testthat
VignetteBuilder: knitr
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2018-04-10 07:19:05 UTC; helen
Author: Helen Ogden [aut, cre]
Maintainer: Helen Ogden <heogden12@gmail.com>
Repository: CRAN
Date/Publication: 2018-04-10 08:10:17 UTC
Built: R 3.3.3; x86_64-w64-mingw32; 2018-04-22 16:50:48 UTC; windows
Archs: i386, x64
