createowl

.createowl

Create method object for Outcome Weighted Learning

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

createowl function

<dl><dt>kernel</dt>
<dd>Kernel object</dd>
<dt>txVec</dt>
<dd>Vector of tx coded as -1/1</dd>
<dt>response</dt>
<dd>Vector of responses</dd>
<dt>prWgt</dt>
<dd>Vector of propensity for tx received</dd>
<dt>surrogate</dt>
<dd>Surrogate object indicating surrogate loss-function</dd>
<dt>guess</dt>
<dd>Vector of estimated regime parameters</dd>
<dt>mu</dt>
<dd>Matrix of outcome regression (zero/ignored)</dd></dl>

Arguments

Create method object for Outcome Weighted Learning — createowl

<dl>

<dt>kernel</dt>
<dd>Kernel object</dd>


<dt>txVec</dt>
<dd>Vector of tx coded as -1/1</dd>


<dt>response</dt>
<dd>Vector of responses</dd>


<dt>prWgt</dt>
<dd>Vector of propensity for tx received</dd>


<dt>surrogate</dt>
<dd>Surrogate object indicating surrogate loss-function</dd>


<dt>guess</dt>
<dd>Vector of estimated regime parameters</dd>


<dt>mu</dt>
<dd>Matrix of outcome regression (zero/ignored)</dd>

</dl>

createowl: Create method object for Outcome Weighted Learning

Description

Usage

Value

Arguments