intersperse

an object inheriting from class <code>"epidata"</code>.

epidata

a numeric vector of time points inside the observation period of the
    <code>epidata</code>.

stoptimes

This function modifies an object inheriting from class <code>"epidata"</code> such 
  that it features the specified stop time points.  For this purpose, the time 
  interval in the event history into which the new stop falls will be splitted 
  up into two parts, one block for the time period until the new stop -- where 
  no infection or removal occurs -- and the other block for the time period 
  from the new stop to the end of the original interval.Main application is to enable the use of <code>knots</code> in <code>twinSIR</code>, which
  are not existing stop time points in the <code>"epidata"</code> object.

manip

spatial

twinSIR_epidata_intersperse

A package implementing 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 for
        surveillance data, or continuous-space point process data such
        as the occurrence of disease or earthquakes. Main 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 of 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), Paul et
        al (2008) and Paul and Held (2011) are provided. A novel CUSUM
        approach combining logistic and multinomial logistic modelling
        is also included.  Continuous self-exciting spatio-temporal
        point processes are modeled through additive-multiplicative
        conditional intensities as described in H�hle (2009)
        ("twinSIR", discrete space) and Meyer et al (2012) ("twinstim",
        continuous space).  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.

twinSIR_epidata_intersperse: Impute Blocks for Extra Stops in `"epidata"` Objects

Description

Usage

Arguments

Value

Examples