Learning-class

Class <code>Learning</code> contains results for a learning analysis with one 
 regime.

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

Learning-class function

<dl>
<dt><code>txInfo</code></dt>
<dd>Feasible tx information</dd></dl>
<dt><code>propen</code></dt>
<dd>Propensity regression analysis</dd>
<dt><code>outcome</code></dt>
<dd>Outcome regression analysis</dd>
<dt><code>optim</code></dt>
<dd>Optimization analysis</dd>

Slots

Class Learning — Learning-class

<dl>
<dt><code>txInfo</code></dt>
<dd>Feasible tx information</dd>


<dt><code>propen</code></dt>
<dd>Propensity regression analysis</dd>


<dt><code>outcome</code></dt>
<dd>Outcome regression analysis</dd>


<dt><code>optim</code></dt>
<dd>Optimization analysis</dd>


</dl>

Learning-class: Class `Learning`

Description

Arguments

Slots