Regime-class

Class <code>Regime</code> holds information regarding regimes communicated 
 through functions.

internal

Methods to estimate dynamic treatment regimes using Interactive
Q-Learning, Q-Learning, weighted learning, and value-search methods based on
Augmented Inverse Probability Weighted Estimators and Inverse Probability
Weighted Estimators. Dynamic Treatment Regimes: Statistical Methods for
Precision Medicine, Tsiatis, A. A., Davidian, M. D., Holloway, S. T., and Laber, E. B.,
Chapman & Hall/CRC Press, 2020, ISBN:978-1-4987-6977-8.

Shannon Holloway

DynTxRegime

Methods for Estimating Optimal Dynamic Treatment Regimes

Regime-class function

<dl>
<dt><code>nVars</code></dt>
<dd>An integer. The number of parameters to be estimated</dd></dl>
<dt><code>vNames</code></dt>
<dd>A character. The names of the parameters to be estimated</dd>
<dt><code>func</code></dt>
<dd>A function. The user specified function that defines the regime</dd>
<dt><code>pars</code></dt>
<dd>A numeric. The estimated parameters</dd>

Slots

Class Regime — Regime-class

<dl>
<dt><code>nVars</code></dt>
<dd>An integer. The number of parameters to be estimated</dd>


<dt><code>vNames</code></dt>
<dd>A character. The names of the parameters to be estimated</dd>


<dt><code>func</code></dt>
<dd>A function. The user specified function that defines the regime</dd>


<dt><code>pars</code></dt>
<dd>A numeric. The estimated parameters</dd>


</dl>

Regime-class: Class `Regime`

Description

Arguments

Slots