The intention of the R-package surveillance is to provide open source software for the temporal and spatio-temporal visualization, modelling and monitoring of epidemic phenomena. This includes count, binary and categorical data time series as well as continuous-time processes having discrete or continuous spatial resolution.
Keywords for this software
References in zbMATH (referenced in 10 articles , 2 standard articles )
Showing results 1 to 10 of 10.
- Paiva, Thais; Assunção, Renato; Simões, Taynãna: Prospective space-time surveillance with cumulative surfaces for geographical identification of the emerging cluster (2015)
- Salmon, Maëlle; Schumacher, Dirk; Stark, Klaus; Höhle, Michael: Bayesian outbreak detection in the presence of reporting delays (2015)
- Meyer, Sebastian; Held, Leonhard: Power-law models for infectious disease spread (2014)
- Manitz, Juliane; Höhle, Michael: Bayesian outbreak detection algorithm for monitoring reported cases of campylobacteriosis in Germany (2013)
- Mehmood, Rashid; Riaz, Muhammad; Does, Ronald J.M.M.: Efficient power computation for $r$ out of $m$ runs rules schemes (2013)
- Meyer, Sebastian; Elias, Johannes; Höhle, Michael: A space-time conditional intensity model for invasive meningococcal disease occurrence (2012)
- Choi, Byeong Yeob; Kim, Ho; Go, Un Yeong; Jeong, Jong-Hyeon; Lee, Jae Won: Comparison of various statistical methods for detecting disease outbreaks (2010)
- Assunção, Renato; Correa, Thais: Surveillance to detect emerging space-time clusters (2009)
- Höhle, Michael; Paul, Michaela: Count data regression charts for the monitoring of surveillance time series (2008)
- Höhle, Michael: Surveillance: An R package for the monitoring of infectious diseases (2007)