Nowcasting by Bayesian Smoothing R package NobBS version 1.1.1 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>. Software Depends: R (>= 3.3.0) Imports: dplyr, rlang, rjags, coda, magrittr Suggests: knitr, rmarkdown, scoringutils (>= 2.0.0), ggplot2 Rodrigo Zepeda Tello <rzepeda17@gmail.com> Comprehensive R Archive Network (CRAN) 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] MIT + file LICENSE (https://CRAN.R-project.org/package=NobBS/LICENSE) 2026-06-01 application/tgz https://CRAN.R-project.org/package=NobBS doi:10.32614/CRAN.package.NobBS