DESCRIPTION

Package: ctas
Type: Package
Title: The package is used to identify anomalous clinical time series
Version: 0.3.0
Authors@R: c(
  person("Pekka", "Tiikkainen",
    role = c("aut", "cre"),
    email = "pekka.tiikkainen@bayer.com"),
  person("Björn", "Koneswarakantha",
    role = c("aut"),
    email = "bjoern.koneswarakantha@roche.com"),
  person("Bayer Pharmaceuticals",
    role = "cph")
  )
Description: The package is used to identify anomalies in clinical time series.
    The main goal is to flag sites whose data is different from other sites in the study
    but also outlying individual subjects can be identified with the results generated.
    See details in the provided PHUSE EU Connect 2022 resources.
License: MIT + file LICENSE
Encoding: UTF-8
Depends:
    dplyr,
    R (>= 3.5.0)
LazyData: true
RoxygenNote: 7.3.2
Imports: 
    dbscan,
    rlang,
    stringr,
    tidyr,
    lme4,
    merTools
Suggests: 
    testthat (>= 3.0.0),
    purrr,
    knitr,
    rmarkdown,
    pkgdown
Config/testthat/edition: 3
URL:
    https://phuse.s3.eu-central-1.amazonaws.com/Archive/2022/Connect/EU/Belfast/PRE_AR04.pdf,
    https://phuse.s3.eu-central-1.amazonaws.com/Archive/2022/Connect/EU/Belfast/PAP_AR04.pdf