Package: glmmrOptim
Type: Package
Title: Approximate Optimal Experimental Designs Using Generalised
        Linear Mixed Models
Version: 0.2.4
Date: 2023-04-19
Authors@R: c(person("Sam", "Watson", email = "S.I.Watson@bham.ac.uk",
                  role = c("aut", "cre")),
             person("Yi", "Pan", email = "ypan1988@gmail.com",
                  role = c("aut")))
Maintainer: Sam Watson <S.I.Watson@bham.ac.uk>
Description: Optimal design analysis algorithms for any study design that can be represented or
  modelled as a generalised linear mixed model including cluster randomised trials,
  cohort studies, spatial and temporal epidemiological studies, and split-plot designs.
  See <https://github.com/samuel-watson/glmmrBase/blob/master/README.md> for a
  detailed manual on model specification. A detailed discussion of the methods in this
  package can be found in Watson and Pan (2022) <arXiv:2207.09183>.
License: GPL (>= 2)
Imports: methods, Rcpp (>= 1.0.7), digest
LinkingTo: Rcpp (>= 1.0.7), RcppEigen, glmmrBase (>= 0.2.5)
RoxygenNote: 7.2.3
NeedsCompilation: yes
Author: Sam Watson [aut, cre],
  Yi Pan [aut]
URL: https://github.com/samuel-watson/glmmrOptim
BugReports: https://github.com/samuel-watson/glmmrOptim/issues
Suggests: testthat, CVXR
Biarch: true
Depends: R (>= 3.4.0), Matrix, glmmrBase
SystemRequirements: GNU make
Encoding: UTF-8
Packaged: 2023-04-20 08:57:47 UTC; samue
Repository: CRAN
Date/Publication: 2023-04-20 09:20:02 UTC
Built: R 4.1.2; x86_64-apple-darwin17.0; 2023-04-21 11:36:26 UTC; unix
Archs: glmmrOptim.so.dSYM
