newModelExport

Creates and initializes a model object based on the provided parameters.
This allows direct creation and inspection of model objects without running MCMC.
Returns a list with all model parameter values for verification.

Provides Bayesian inference methods for infectious disease transmission
models in healthcare settings. Implements Markov Chain Monte Carlo (MCMC) algorithms
for estimating transmission parameters from patient-level data including admission,
discharge, and testing events as described in Thomas 'et al.' (2015) <doi:10.1093/imammb/dqt021>.

Andrew Redd

bayestransmission

Bayesian Transmission Models

Alun Thomas

University of Utah 

CDC's Center for Forecasting and Outbreak Analytics 

newModelExport function

<dl><dt>modelParameters</dt>
<dd>List of model parameters, including:<ul>
<li><code>modname</code> Name of the model (e.g., "LogNormalModel", "LinearAbxModel", "LinearAbxModel2", "MixedModel")</li>
<li><code>nstates</code> Number of states in the model</li>
<li><code>nmetro</code> Number of metropolis steps</li>
<li><code>forward</code> Forward parameter</li>
<li><code>cheat</code> Cheat parameter</li>
</ul></dd>
<dt>verbose</dt>
<dd>Print progress messages (default: false)</dd></dl>

Arguments

Create a new model object — newModelExport

<dl>

<dt>modelParameters</dt>
<dd>List of model parameters, including:<ul>
<li><code>modname</code> Name of the model (e.g., "LogNormalModel", "LinearAbxModel", "LinearAbxModel2", "MixedModel")</li>
<li><code>nstates</code> Number of states in the model</li>
<li><code>nmetro</code> Number of metropolis steps</li>
<li><code>forward</code> Forward parameter</li>
<li><code>cheat</code> Cheat parameter</li>
</ul></dd>


<dt>verbose</dt>
<dd>Print progress messages (default: false)</dd>

</dl>

newModelExport: Create a new model object

Description

Usage

Value

Arguments