Statistical methods for the modeling and monitoring of time series
of counts, proportions and categorical data, as well as for the modeling
of continuoustime point processes of epidemic phenomena.
The monitoring methods focus on aberration detection in count data time
series from public health surveillance of communicable diseases, but
applications could just as well originate from environmetrics,
reliability engineering, econometrics, or social sciences. The package
implements many typical outbreak detection procedures such as the
(improved) Farrington algorithm, or the negative binomial GLRCUSUM
method of Hhle and Paul (2008)
Package details 


Author  Michael Hhle [aut, ths], Sebastian Meyer [aut, cre], Michaela Paul [aut], Leonhard Held [ctb, ths], Howard Burkom [ctb], Thais Correa [ctb], Mathias Hofmann [ctb], Christian Lang [ctb], Juliane Manitz [ctb], Andrea Riebler [ctb], Daniel Sabans Bov [ctb], Malle Salmon [ctb], Dirk Schumacher [ctb], Stefan Steiner [ctb], Mikko Virtanen [ctb], Wei Wei [ctb], Valentin Wimmer [ctb], R Core Team [ctb] (A few code segments are modified versions of code from base R) 
Date of publication  20171006 20:34:46 UTC 
Maintainer  Sebastian Meyer <[email protected]> 
License  GPL2 
Version  1.15.0 
URL  http://surveillance.RForge.Rproject.org/ 
Package repository  View on CRAN 
Installation 
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