EARLIPWE-class

Efficient Augmentation and Relaxation Learning with 
Inverse Propensity Weighted Estimator

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.

Shannon Holloway

DynTxRegime

Methods for Estimating Optimal Dynamic Treatment Regimes

EARLIPWE-class function

Objects can be created by calls of the form <code>new(&quot;EARLIPWE&quot;, ...)</code>.
These objects are for convenience in package development
and should not be created by users.

Objects from the Class

Classes <code>&quot;<a rd-options="" href="/link/EARL-class?package=DynTxRegime&version=3.01" data-mini-rdoc="DynTxRegime::EARL-class">EARL-class</a>&quot;</code> and
<code>&quot;<a rd-options="" href="/link/PropensityOnly-class?package=DynTxRegime&version=3.01" data-mini-rdoc="DynTxRegime::PropensityOnly-class">PropensityOnly-class</a>&quot;</code> directly.Class <code>&quot;<a rd-options="" href="/link/DynTxRegime-class?package=DynTxRegime&version=3.01" data-mini-rdoc="DynTxRegime::DynTxRegime-class">DynTxRegime-class</a>&quot;</code> by class <code>&quot;<a rd-options="" href="/link/EARL-class?package=DynTxRegime&version=3.01" data-mini-rdoc="DynTxRegime::EARL-class">EARL-class</a>&quot;</code>,
distance 2.

Extends

<dl class="dl-horizontal"><dt>DTRstep</dt><dd><code>signature(object = &quot;EARLIPWE&quot;)</code>: 
 Retrieve descripton of method. </dd><dt>print</dt><dd><code>signature(x = &quot;EARLIPWE&quot;)</code>: 
 Print key results of method. </dd><dt>show</dt><dd><code>signature(object = &quot;EARLIPWE&quot;)</code>: 
 Show key results of method. </dd><dt>summary</dt><dd><code>signature(object = &quot;EARLIPWE&quot;)</code>: 
 Retrieve key summary information of method. </dd></dl>

EARLIPWE-class: Class

Description

Arguments

Objects from the Class

Extends

Methods

Examples