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.

Methods for Estimating Optimal Dynamic Treatment Regimes

package-ubuntu-20.04-r-4.0.5#cran#DynTxRegime-4.10

Class <code>Kernel</code> holds information regarding the decision function kernel

<dl>
<dt><code>model</code></dt>
<dd>
An formula. Defines the covariates of the kernel.
</dd>
<dt><code>X</code></dt>
<dd>
A matrix. The covariates of the kernel
</dd>
<dt><code>kparam</code></dt>
<dd>
ANY. The kernel parameter
</dd>
</dl>

package-ubuntu-20.04-r-4.0.5#cran#DynTxRegime-4.10#docs#Kernel-class

Kernel-class

Description

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DynTxRegime

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