Package: NobBS Title: Nowcasting by Bayesian Smoothing Version: 1.1.2 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) . 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 Config/pak/sysreqs: jags Repository: https://sarahhbellum.r-universe.dev Date/Publication: 2026-06-03 15:58:55 UTC RemoteUrl: https://github.com/sarahhbellum/nobbs RemoteRef: HEAD RemoteSha: f45caee94292f0c4749fd794ee2fd5f224acdfbd NeedsCompilation: no Packaged: 2026-07-03 09:12:14 UTC; root 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