show,SimInf_pmcmc-method

Display a summary of a particle Markov chain Monte Carlo (PMCMC)
analysis, including the number of iterations, number of particles,
mixing proportion for the adaptive proposal, acceptance ratio, and
posterior quantiles (2.5
standard deviation for each estimated parameter.

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> or the Particle Markov Chain Monte
Carlo ('PMCMC') algorithm of 'Andrieu' and others (2010)
<doi:10.1111/j.1467-9868.2009.00736.x>.

Stefan Widgren

SimInf

A Framework for Data-Driven Stochastic Disease Spread
Simulations

Robin Eriksson

Stefan Engblom

Pavol Bauer

Thomas Rosendal

Ivana Rodriguez Ewerlöf

Attractive Chaos 

show,SimInf_pmcmc-method function

<dl><dt>object</dt>
<dd>The <code>SimInf_pmcmc</code> object to
display.</dd></dl>

Arguments

Brief summary of a SimInf_pmcmc object — show,SimInf_pmcmc-method

<dl>

<dt>object</dt>
<dd>The <code>SimInf_pmcmc</code> object to
display.</dd>

</dl>

show,SimInf_pmcmc-method: Brief summary of a `SimInf_pmcmc` object

Description

Usage

Value

Arguments

See Also