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. (2019) <doi:10.1101/663823>.
| Version: | 0.1.0 |
| Depends: | R (≥ 3.3.0) |
| Imports: | dplyr, rjags, coda, magrittr |
| Published: | 2020-03-03 |
| Author: | Sarah McGough [aut, cre], Nicolas Menzies [aut], Marc Lipsitch [aut], Michael Johansson [aut] |
| Maintainer: | Sarah McGough <sfm341 at mail.harvard.edu> |
| License: | MIT + file LICENSE |
| NeedsCompilation: | no |
| SystemRequirements: | JAGS (http://mcmc-jags.sourceforge.net/) for analysis of Bayesian hierarchical models |
| Materials: | README NEWS |
| CRAN checks: | NobBS results |
| Reference manual: | NobBS.pdf |
| Package source: | NobBS_0.1.0.tar.gz |
| Windows binaries: | r-devel: NobBS_0.1.0.zip, r-release: NobBS_0.1.0.zip, r-oldrel: NobBS_0.1.0.zip |
| macOS binaries: | r-release: NobBS_0.1.0.tgz, r-oldrel: NobBS_0.1.0.tgz |
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