simulate_dat

This function simulates a dynamic network over one or multiple
time steps for TERGMs or one or multiple cross-sectional network
panels for ERGMs, for use in <code>netsim</code> modeling.
Network statistics are also extracted and saved if
<code>save.nwstats == TRUE</code> and
<code>resimulate.network == FALSE</code>.

internal

netUtils

Tools for simulating mathematical models of infectious disease dynamics.
Epidemic model classes include deterministic compartmental models, stochastic
individual-contact models, and stochastic network models. Network models use the
robust statistical methods of exponential-family random graph models (ERGMs)
from the Statnet suite of software packages in R. Standard templates for epidemic
modeling include SI, SIR, and SIS disease types. EpiModel features an API for
extending these templates to address novel scientific research aims. Full
methods for EpiModel are detailed in Jenness et al. (2018, <doi:10.18637/jss.v084.i08>).

Samuel Jenness

EpiModel

Mathematical Modeling of Infectious Disease Dynamics

Steven M. Goodreau

Martina Morris

Adrien Le Guillou

Chad Klumb

Skye Bender-deMoll

simulate_dat function

<dl><dt>dat</dt>
<dd>Main <code>netsim_dat</code> object containing a <code>networkDynamic</code>
object and other initialization information passed from
<code>netsim</code>.</dd>
<dt>at</dt>
<dd>Current time step.</dd>
<dt>network</dt>
<dd>index of the network to simulate</dd>
<dt>nsteps</dt>
<dd>number of time steps to simulate</dd></dl>

Arguments

Simulate a Network for a Specified Number of Time Steps — simulate_dat

<dl>

<dt>dat</dt>
<dd>Main <code>netsim_dat</code> object containing a <code>networkDynamic</code>
object and other initialization information passed from
<code>netsim</code>.</dd>


<dt>at</dt>
<dd>Current time step.</dd>


<dt>network</dt>
<dd>index of the network to simulate</dd>


<dt>nsteps</dt>
<dd>number of time steps to simulate</dd>

</dl>

simulate_dat: Simulate a Network for a Specified Number of Time Steps

Description

Usage

Value

Arguments