OptimalObj-class

Class <code>OptimalObj</code> stores the estimated optimal Tx, decision functions
and estimated value under a common name.

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

OptimalObj-class function

<dl>
<dt><code>optimal</code></dt>
<dd>ANY - must be <code>OptimalInfo</code> or 
<code>DecisionPointList</code> of <code>OptimalInfo</code></dd></dl>

Slots

Class OptimalObj — OptimalObj-class

<dl>
<dt><code>optimal</code></dt>
<dd>ANY - must be <code>OptimalInfo</code> or 
<code>DecisionPointList</code> of <code>OptimalInfo</code></dd>


</dl>

OptimalObj-class: Class `OptimalObj`

Description

Arguments

Slots