MethodObject-class

Class <code>MethodObject</code> stores parameters required for optimization step

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

MethodObject-class function

<dl>
<dt><code>x</code></dt>
<dd>Matrix of covariates for kernel</dd></dl>
<dt><code>surrogate</code></dt>
<dd>The Surrogate for the loss-function</dd>
<dt><code>pars</code></dt>
<dd>Vector of regime parameters</dd>
<dt><code>kernel</code></dt>
<dd>The Kernel defining the decision function</dd>

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Class MethodObject — MethodObject-class

<dl>
<dt><code>x</code></dt>
<dd>Matrix of covariates for kernel</dd>


<dt><code>surrogate</code></dt>
<dd>The Surrogate for the loss-function</dd>


<dt><code>pars</code></dt>
<dd>Vector of regime parameters</dd>


<dt><code>kernel</code></dt>
<dd>The Kernel defining the decision function</dd>


</dl>

MethodObject-class: Class `MethodObject`

Description

Arguments

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