continue

continue,SimInf_abc-method

The <code>SimInf_abc</code> to continue from.

object

The number of generations of ABC-SMC to run.

ngen

Further arguments to be passed to
<code>SimInf_abc@fn</code>.

prints diagnostic messages when <code>TRUE</code>. The
default is to retrieve the global option <code>verbose</code> and
use <code>FALSE</code> if it is not set.

verbose

Provides an efficient and very flexible framework to
conduct data-driven epidemiological modeling in realistic large
scale disease spread simulations. The framework integrates
infection dynamics in subpopulations as continuous-time Markov
chains using the Gillespie stochastic simulation algorithm and
incorporates available data such as births, deaths and movements
as scheduled events at predefined time-points. Using C code for
the numerical solvers and 'OpenMP' (if available) to divide work
over multiple processors ensures high performance when simulating
a sample outcome. One of our design goals was to make the package
extendable and enable usage of the numerical solvers from other R
extension packages in order to facilitate complex epidemiological
research. The package contains template models and can be extended
with user-defined models. For more details see the paper by
Widgren, Bauer, Eriksson and Engblom (2019)
<doi:10.18637/jss.v091.i12>. The package also provides
functionality to fit models to time series data using the
Approximate Bayesian Computation Sequential Monte Carlo
('ABC-SMC') algorithm of Toni and others (2009)
<doi:10.1098/rsif.2008.0172>.

continue: Run more generations of ABC SMC

Description

Usage

Arguments

Value