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NobBS: Nowcasting by Bayesian Smoothing

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>.

Version:1.1.0
Depends:R (≥ 3.3.0)
Imports:dplyr,rlang,rjags,coda,magrittr
Suggests:knitr,rmarkdown,scoringutils (≥ 2.0.0),ggplot2
Published:2025-05-07
DOI:10.32614/CRAN.package.NobBS
Author:Rami Yaari [cre, aut], Rodrigo Zepeda Tello [aut, ctb], Sarah McGough [aut, ctb], Nicolas Menzies [aut], Marc Lipsitch [aut], Michael Johansson [aut], Teresa Yamana [ctb], Matteo Perini [ctb]
Maintainer:Rami Yaari <ry2460 at cumc.columbia.edu>
License:MIT + fileLICENSE
NeedsCompilation:no
SystemRequirements:JAGS (http://mcmc-jags.sourceforge.net/) foranalysis of Bayesian hierarchical models
Materials:README,NEWS
CRAN checks:NobBS results

Documentation:

Reference manual:NobBS.html ,NobBS.pdf
Vignettes:Handling Batched Reporting in Nowcast Models (source,R code)
Accounting for Day-of-the-Week Effect in Nowcast Models (source,R code)
Calculating Weighted Interval Score for Nowcast Models (source,R code)

Downloads:

Package source: NobBS_1.1.0.tar.gz
Windows binaries: r-devel:NobBS_1.1.0.zip, r-release:NobBS_1.1.0.zip, r-oldrel:NobBS_1.1.0.zip
macOS binaries: r-release (arm64):NobBS_1.1.0.tgz, r-oldrel (arm64):NobBS_1.1.0.tgz, r-release (x86_64):NobBS_1.1.0.tgz, r-oldrel (x86_64):NobBS_1.1.0.tgz
Old sources: NobBS archive

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=NobBSto link to this page.


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