Package: oncomsm
Type: Package
Title: Bayesian Multi-State Models for Early Oncology
Version: 0.1.4
Authors@R: c(
    person("Kevin", "Kunzmann",
      role = c("aut", "cre"),
      email = "kevin.kunzmann@boehringer-ingelheim.com",
      comment = c(ORCID = "0000-0002-1140-7143")
    ),
    person("Karthik", "Ananthakrishnan",
      role = c("ctb")
    ),
    person(
      "Boehringer Ingelheim Ltd.",
      role = c("cph", "fnd")
    )
  )
Description: Implements methods to fit a parametric Bayesian multi-state model
    to tumor response data.
    The model can be used to sample from the predictive distribution to impute
    missing data and calculate probability of success for custom decision
    criteria in early clinical trials during an ongoing trial.
    The inference is implemented using 'stan'.
Language: en-US
License: Apache License 2.0
Encoding: UTF-8
RoxygenNote: 7.2.3
Biarch: true
Depends: R (>= 3.6)
Imports: methods, Rcpp, RcppNumerical (>= 0.4), rstan (>= 2.18), rlang
        (>= 0.4), magrittr, tibble, dplyr, tidyr, purrr, furrr,
        stringr, ggplot2, checkmate, rstantools
SystemRequirements: GNU make
LinkingTo: BH (>= 1.66.0), Rcpp, RcppEigen (>= 0.3), RcppNumerical (>=
        0.4), rstan (>= 2.18), StanHeaders (>= 2.18), RcppParallel
Suggests: rmarkdown, knitr, testthat (>= 3.0.0), patchwork, bhmbasket,
        vdiffr, DiagrammeR, future, doFuture, doRNG, rjags
VignetteBuilder: knitr
Config/testthat/edition: 3
URL: https://boehringer-ingelheim.github.io/oncomsm/,
        https://github.com/Boehringer-Ingelheim/oncomsm
BugReports: https://github.com/Boehringer-Ingelheim/oncomsm/issues
NeedsCompilation: yes
Packaged: 2023-04-16 23:24:10 UTC; kunzmann
Author: Kevin Kunzmann [aut, cre] (<https://orcid.org/0000-0002-1140-7143>),
  Karthik Ananthakrishnan [ctb],
  Boehringer Ingelheim Ltd. [cph, fnd]
Maintainer: Kevin Kunzmann <kevin.kunzmann@boehringer-ingelheim.com>
Repository: CRAN
Date/Publication: 2023-04-17 07:00:02 UTC
Built: R 4.1.2; x86_64-apple-darwin17.0; 2023-04-18 11:39:13 UTC; unix
Archs: oncomsm.so.dSYM
