DynTxRegime (version 3.01)

OptimKernel-class: Class

Description

Basic optimization object for weighted learning methods when kernels are used.

Objects from the Class

Objects can be created by calls of the form new("OptimKernel", ...). These objects are for convenience in package development and should not be created by users.

Slots

covariates:

Object of class "matrix." The training data covariates matrix for kernel.

kernel:

Object of class "character." The description of kernel used.

kParam:

Object of class "numeric." The kernel parameter used.

Extends

Class "OptimBasic-class" directly.

Methods

optimObj

signature(object = "OptimKernel"): The object returned by optimization routine.

.predictOptimalTx

signature(x = "OptimKernel", newdata = "matrix"): Predict optimal treatment for new data.

.predictOptimalTx

signature(x = "OptimKernel", newdata = "data.frame"): Predict optimal treatment for new data.

print

signature(x = "OptimKernel"): Print key results of optimization.

show

signature(object = "OptimKernel"): Show key results of optimization.

summary

signature(object = "OptimKernel"): Return summary information about optimization.

Examples

showClass("OptimKernel")