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. (2019) .


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Reference manual

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install.packages("NobBS")

0.1.0 by Sarah McGough, 4 months ago


Browse source code at https://github.com/cran/NobBS


Authors: Sarah McGough [aut, cre] , Nicolas Menzies [aut] , Marc Lipsitch [aut] , Michael Johansson [aut]


Documentation:   PDF Manual  


MIT + file LICENSE license


Imports dplyr, rjags, coda, magrittr

System requirements: JAGS (http://mcmc-jags.sourceforge.net/) for analysis of Bayesian hierarchical models


See at CRAN