[,sts-method

[,sts,ANY,ANY,ANY-method

<code>"["</code>-methods, i.e., extraction or subsetting of the
 <code>"<links4class>sts</links4class>"</code> class in package <pkg>surveillance</pkg>. Note that <code>[&lt;-</code> methods (i.e. subassignments) are
 currently not supported. The <code>drop</code> argument is always <code>FALSE</code>.

methods

array

[,sts-methods

Statistical methods for the modeling and monitoring of time series
 of counts, proportions and categorical data, as well as for the modeling
 of continuous-time 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 GLR-CUSUM
 method of H�hle and Paul (2008) <doi:10.1016/j.csda.2008.02.015>.
 A novel CUSUM approach combining logistic and multinomial logistic
 modeling is also included. The package contains several real-world data
 sets, the ability to simulate outbreak data, and to visualize the
 results of the monitoring in a temporal, spatial or spatio-temporal
 fashion. A recent overview of the available monitoring procedures is
 given by Salmon et al. (2016) <doi:10.18637/jss.v070.i10>.
 For the retrospective analysis of epidemic spread, the package provides
 three endemic-epidemic modeling frameworks with tools for visualization,
 likelihood inference, and simulation. 'hhh4' estimates models for
 (multivariate) count time series following Paul and Held (2011)
 <doi:10.1002/sim.4177> and Meyer and Held (2014) <doi:10.1214/14-AOAS743>.
 'twinSIR' models the susceptible-infectious-recovered (SIR) event
 history of a fixed population, e.g, epidemics across farms or networks,
 as a multivariate point process as proposed by H�hle (2009)
 <doi:10.1002/bimj.200900050>. 'twinstim' estimates self-exciting point
 process models for a spatio-temporal point pattern of infective events,
 e.g., time-stamped geo-referenced surveillance data, as proposed by
 Meyer et al. (2012) <doi:10.1111/j.1541-0420.2011.01684.x>.
 A recent overview of the implemented space-time modeling frameworks
 for epidemic phenomena is given by Meyer et al. (2015)
 <http://arxiv.org/abs/1411.0416>.

Sebastian Meyer

surveillance

Temporal and Spatio-Temporal Modeling and Monitoring of Epidemic
        Phenomena

[,sts-methods function

Extraction and Subsetting of <code>"sts"</code> Objects

[,sts-methods: Extraction and Subsetting of `"sts"` Objects

Description

Arguments

Examples