Author: tille Date: 2015-11-24 21:59:16 +0000 (Tue, 24 Nov 2015) New Revision: 20540
Modified: trunk/packages/R/r-cran-surveillance/trunk/debian/changelog trunk/packages/R/r-cran-surveillance/trunk/debian/control Log: Update description Modified: trunk/packages/R/r-cran-surveillance/trunk/debian/changelog =================================================================== --- trunk/packages/R/r-cran-surveillance/trunk/debian/changelog 2015-11-24 21:47:58 UTC (rev 20539) +++ trunk/packages/R/r-cran-surveillance/trunk/debian/changelog 2015-11-24 21:59:16 UTC (rev 20540) @@ -1,6 +1,7 @@ r-cran-surveillance (1.10-0-2) UNRELEASED; urgency=medium * Update copyright information + * Update description -- Andreas Tille <[email protected]> Tue, 24 Nov 2015 22:47:03 +0100 Modified: trunk/packages/R/r-cran-surveillance/trunk/debian/control =================================================================== --- trunk/packages/R/r-cran-surveillance/trunk/debian/control 2015-11-24 21:47:58 UTC (rev 20539) +++ trunk/packages/R/r-cran-surveillance/trunk/debian/control 2015-11-24 21:59:16 UTC (rev 20540) @@ -35,16 +35,37 @@ r-cran-spdep, r-cran-memoise, r-cran-maxlik, - r-cran-rcpp, - r-cran-spdep -Description: development and the evaluation of epidemiological outbreak detection algorithms - The R-package 'surveillance' is a framework for the development and the - evaluation of outbreak detection algorithms in univariate and multivariate - routine collected public health surveillance data. It is hosted on CRAN.. + r-cran-rcpp +Description: Temporal and Spatio-Temporal Modeling and Monitoring of Epidemic Phenomena + Implementation of statistical methods for the modeling and change-point + detection in time series of counts, proportions and categorical data, as + well as for the modeling of continuous-time epidemic phenomena, e.g., + discrete-space setups such as the spatially enriched + Susceptible-Exposed-Infectious-Recovered (SEIR) models, or + continuous-space point process data such as the occurrence of infectious + diseases. Main focus is on outbreak detection in count data time series + originating from public health surveillance of communicable diseases, + but applications could just as well originate from environmetrics, + reliability engineering, econometrics or social sciences. . - The intention of the R-package surveillance is to provide open source - software for the visualization and monitoring of count data time series - in public health surveillance. Potential users are epidemiologists and - others working in applied infectious disease epidemiology. - Furthermore, surveillance also provides a data structure and framework - for methodological developments of surveillance algorithms. + Currently, the package contains implementations of many typical + outbreak detection procedures such as Farrington et al (1996), Noufaily + et al (2012) or the negative binomial LR-CUSUM method described in Höhle + and Paul (2008). A novel CUSUM approach combining logistic and + multinomial logistic modelling is also included. Furthermore, inference + methods for the retrospective infectious disease models in Held et al + (2005), Held et al (2006), Paul et al (2008), Paul and Held (2011), Held + and Paul (2012), and Meyer and Held (2014) are provided. + . + Continuous self-exciting spatio-temporal point processes are modeled + through additive-multiplicative conditional intensities as described in + Höhle (2009) ('twinSIR', discrete space) and Meyer et al (2012) + ('twinstim', continuous space). + . + The package contains several real-world data sets, the ability to + simulate outbreak data, visualize the results of the monitoring in + temporal, spatial or spatio-temporal fashion. + . + Note: Using the 'boda' algorithm requires the 'INLA' package, which + should be installed automatically through the specified + Additional_repositories, if uninstalled dependencies are also requested. _______________________________________________ debian-med-commit mailing list [email protected] http://lists.alioth.debian.org/cgi-bin/mailman/listinfo/debian-med-commit
