InsituParams

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 

InsituParams function

<dl><dt>probs</dt>
<dd>The probability of the individual being in each state.</dd>
<dt>priors</dt>
<dd>The prior probability of the individual being in each state.</dd>
<dt>doit</dt>
<dd>A flag indicating if the rate(s) should be updated in the MCMC.</dd>
<dt>nstates</dt>
<dd>The number of states (2 or 3). If NULL, inferred from probs length.
For 2-state models, uses <code>c(uncolonized, latent=0, colonized)</code>.
For 3-state models, uses <code>c(uncolonized, latent, colonized)</code>.</dd></dl>

Arguments

InSitu Parameters — InsituParams

<dl>

<dt>probs</dt>
<dd>The probability of the individual being in each state.</dd>


<dt>priors</dt>
<dd>The prior probability of the individual being in each state.</dd>


<dt>doit</dt>
<dd>A flag indicating if the rate(s) should be updated in the MCMC.</dd>


<dt>nstates</dt>
<dd>The number of states (2 or 3). If NULL, inferred from probs length.
For 2-state models, uses <code>c(uncolonized, latent=0, colonized)</code>.
For 3-state models, uses <code>c(uncolonized, latent, colonized)</code>.</dd>

</dl>

InsituParams: InSitu Parameters

Description

Usage

Value

Arguments

Examples