verbose.dcm

This function prints progress from deterministic compartmental
models simulated with <code>dcm</code> to the console.

internal

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

verbose.dcm function

<dl><dt>x</dt>
<dd>If the <code>type</code> is "startup", then an object of class
<code>control.dcm</code>, otherwise the main <code>df</code> object in <code>dcm</code>
runs.</dd>
<dt>type</dt>
<dd>Progress type, either of "startup" for starting messages before
all runs, or "progress" for time step specific messages.</dd>
<dt>s</dt>
<dd>Current run number, if type is "progress".</dd></dl>

Arguments

Progress Print Module for Deterministic Compartmental Models — verbose.dcm

<dl>

<dt>x</dt>
<dd>If the <code>type</code> is "startup", then an object of class
<code>control.dcm</code>, otherwise the main <code>df</code> object in <code>dcm</code>
runs.</dd>


<dt>type</dt>
<dd>Progress type, either of "startup" for starting messages before
all runs, or "progress" for time step specific messages.</dd>


<dt>s</dt>
<dd>Current run number, if type is "progress".</dd>

</dl>

verbose.dcm: Progress Print Module for Deterministic Compartmental Models

Description

Usage

Arguments