.newClassificationObj

.newClassificationObj,ANY-method

Method calls .newClassificationFit() and stores the result in @classif.

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

.newClassificationObj function

<dl><dt>moClass</dt>
<dd>modeling object(s) defining the classification regression</dd>
<dt>txObj</dt>
<dd>TxObj defining the tx feasible sets</dd>
<dt>...</dt>
<dd>additional arguments. Ignored.</dd>
<dt>data</dt>
<dd>data.frame of covariates and tx received</dd>
<dt>suppress</dt>
<dd>logical indicating user's screen printing preference</dd></dl>

Arguments

Create an Object of Class ClassificationFitObj — .newClassificationObj

<dl>

<dt>moClass</dt>
<dd>modeling object(s) defining the classification regression</dd>


<dt>txObj</dt>
<dd>TxObj defining the tx feasible sets</dd>


<dt>...</dt>
<dd>additional arguments. Ignored.</dd>


<dt>data</dt>
<dd>data.frame of covariates and tx received</dd>


<dt>suppress</dt>
<dd>logical indicating user's screen printing preference</dd>

</dl>

.newClassificationObj: Create an Object of Class `ClassificationFitObj`

Description

Usage

Arguments