sts-class

nrow,sts-method

ncol,sts-method

dim,sts-method

alarms,sts-method

alarms<-,sts-method

upperbound,sts-method

upperbound<-,sts-method

control,sts-method

control<-,sts-method

epoch,sts-method

epoch<-,sts-method

epochInYear,sts-method

observed,sts-method

observed<-,sts-method

population,sts-method

population<-,sts-method

colnames,sts,missing,missing-method

initialize,sts-method

as.data.frame,sts-method

This is a rather leightweight class to implement multivariate time
  series of count used for public health surveillance data. The class
  captures the time series data as well as the spatial layout of the
  regions, where the data originate from.

classes

A package implementing statistical methods for the
        modeling and change-point detection in time series of counts,
        proportions and categorical data. Focus is on outbreak
        detection in count data time series originating from public
        health surveillance of infectious diseases, but applications
        could just as well originate from environmetrics, reliability
        engineering, econometrics or social sciences.  Currently the
        package contains implementations typical outbreak detection
        procedures such as Stroup et. al (1989), Farrington et al,
        (1996), Rossi et al. (1999), Rogerson and Yamada (2001), a
        Bayesian approach, negative binomial CUSUM methods and a
        detector based on generalized likelihood ratios. Furthermore,
        inference methods for the retrospective infectious disease
        model in Held et al. (2005), Held et al. (2006) and Paul et al.
        (2008) are provided. A novel CUSUM approach combining logistic
        and multinomial logistic modelling is also included. The
        package contains several real-world datasets, the ability to
        simulate outbreak data, visualize the results of the monitoring
        in temporal, spatial or spatio-temporal fashion.

sts-class: Class "sts" -- surveillance time series

Description

Arguments

encoding

Examples