sim_nets_t1

This function initializes the networks used in
<code>netsim</code>. The initial edge set for a given network
is obtained either from simulating the cross-sectional model
(if <code>edapprox == TRUE</code>) or from the <code>newnetwork</code>
element of the <code>netest</code> object (if
<code>edapprox == FALSE</code>). Once the initial edge sets are
determined, the first time step is simulated if
<code>resimulate.network == TRUE</code>, and all time steps are
simulated if <code>resimulate.network == FALSE</code>. Initializes the
<code>num(.g2)</code> epi fields used in
<code>edges_correct</code> for computing edge coefficient
adjustments.

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

sim_nets_t1 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></dl>

Arguments

Initialize Networks Used in netsim — sim_nets_t1

<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>

</dl>

sim_nets_t1: Initialize Networks Used in netsim

Description

Usage

Value

Arguments