Package: NobBS
Title: Nowcasting by Bayesian Smoothing
Version: 1.1.1
Authors@R: c(
    person("Sarah", "McGough", email = "sfm341@mail.harvard.edu", role = c("aut", "ctb")),
    person("Nicolas", "Menzies", email = "nmenzies@hsph.harvard.edu", role = "aut"),
    person("Marc", "Lipsitch", email = "mlipsitc@hsph.harvard.edu", role = "aut"),
    person("Michael", "Johansson", email = "mjohansson@cdc.gov", role = "aut"),
    person("Rami", "Yaari", email = "ramiyaari@gmail.com", role = c("aut","ctb")),
    person("Rodrigo", "Zepeda Tello", email = "rzepeda17@gmail.com", role = c("cre","aut","ctb")),
    person("Teresa", "Yamana", email = "tky2104@climate.columbia.edu", role = c("ctb")),
    person("Matteo", "Perini", email = "mperini@climate.columbia.edu", role = c("ctb"))
    )
Description: A Bayesian approach to estimate the number of occurred-but-not-yet-reported cases from incomplete, time-stamped reporting data for disease outbreaks. 'NobBS' learns the reporting delay distribution and the time evolution of the epidemic curve to produce smoothed nowcasts in both stable and time-varying case reporting settings, as described in McGough et al. (2020) <doi:10.1371/journal.pcbi.1007735>.  
Depends: R (>= 3.3.0)
SystemRequirements: JAGS (http://mcmc-jags.sourceforge.net/) for
        analysis of Bayesian hierarchical models
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: dplyr, rlang, rjags, coda, magrittr
RoxygenNote: 7.3.2
Suggests: knitr, rmarkdown, scoringutils (>= 2.0.0), ggplot2
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-05-29 17:10:09 UTC; ry2460
Author: Sarah McGough [aut, ctb],
  Nicolas Menzies [aut],
  Marc Lipsitch [aut],
  Michael Johansson [aut],
  Rami Yaari [aut, ctb],
  Rodrigo Zepeda Tello [cre, aut, ctb],
  Teresa Yamana [ctb],
  Matteo Perini [ctb]
Maintainer: Rodrigo Zepeda Tello <rzepeda17@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-01 14:20:11 UTC
Built: R 4.5.2; ; 2026-06-01 14:46:12 UTC; unix
