Package: tramME
Title: Transformation Models with Mixed Effects
Version: 1.0.7
Date: 2024-11-29
Authors@R: c(person("Balint", "Tamasi", role = c("aut", "cre"),
                    email = "balint.tamasi+tramME@gmail.com",
                    comment = c(ORCID = "0000-0002-2629-7362")),
             person("Torsten", "Hothorn",  role = "ctb",
                    email = "Torsten.Hothorn@R-project.org",
                    comment = c(ORCID = "0000-0001-8301-0471")))
Description: Likelihood-based estimation of mixed-effects transformation models
    using the Template Model Builder ('TMB', Kristensen et al., 2016)
    <doi:10.18637/jss.v070.i05>. The technical details of transformation models
    are given in Hothorn et al. (2018) <doi:10.1111/sjos.12291>. Likelihood
    contributions of exact, randomly censored (left, right, interval) and
    truncated observations are supported. The random effects are assumed to be
    normally distributed on the scale of the transformation function, the
    marginal likelihood is evaluated using the Laplace approximation, and the
    gradients are calculated with automatic differentiation (Tamasi & Hothorn,
    2021) <doi:10.32614/RJ-2021-075>. Penalized smooth shift terms can be
    defined using 'mgcv'.
Depends: R (>= 3.6.0), tram (>= 0.3.2), mlt (>= 1.1.0)
Imports: alabama, Matrix, methods, mgcv (>= 1.8.34), nlme, TMB (>=
        1.7.15), stats, variables (>= 1.0.2), basefun (>= 1.0.6),
        numDeriv, MASS, coneproj, mvtnorm, reformulas
Suggests: lme4 (>= 1.1.19), multcomp, parallel, survival, knitr, coxme,
        ordinal, ordinalCont, gamm4, gamlss.dist, glmmTMB, xtable
LinkingTo: TMB, RcppEigen
VignetteBuilder: knitr
License: GPL-2
URL: http://ctm.R-forge.R-project.org
Encoding: UTF-8
RoxygenNote: 7.3.2
NeedsCompilation: yes
Packaged: 2024-11-29 18:11:40 UTC; balint
Author: Balint Tamasi [aut, cre] (<https://orcid.org/0000-0002-2629-7362>),
  Torsten Hothorn [ctb] (<https://orcid.org/0000-0001-8301-0471>)
Maintainer: Balint Tamasi <balint.tamasi+tramME@gmail.com>
Repository: CRAN
Date/Publication: 2024-11-29 19:10:02 UTC
