Package: glmmrOptim Type: Package Title: Approximate Optimal Experimental Designs Using Generalised Linear Mixed Models Version: 0.5.1 Date: 2026-06-06 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 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 for a detailed manual on model specification. A detailed discussion of the methods in this package can be found in Watson, Hemming, and Girling (2023) . License: GPL (>= 2) Imports: methods, Rcpp (>= 1.0.7), digest LinkingTo: Rcpp (>= 1.0.7), RcppEigen, RcppProgress, glmmrBase (>= 1.0.0), SparseChol (>= 0.2.1), BH, rminqa (>= 0.2.2) RoxygenNote: 7.3.3 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 Biarch: true Depends: R (>= 3.4.0), Matrix, glmmrBase SystemRequirements: GNU make Encoding: UTF-8 Config/pak/sysreqs: make Repository: https://samuel-watson.r-universe.dev Date/Publication: 2026-06-06 16:28:47 UTC RemoteUrl: https://github.com/samuel-watson/glmmroptim RemoteRef: HEAD RemoteSha: 43ceb873744a9f62d484e251f1991bcd7e675b54 Packaged: 2026-07-06 10:44:24 UTC; root