Description

Class .earl stores parameters required for EARL optimization step.

Slots

x

Matrix of covariates for kernel

wp

Vector of positive weights

wn

Vector of negative weights

mu

Matrix of outcome regression

txVec

Vector of treatment coded as -1/1

invPi

Vector of inverse propensity for treatment received

response

Vector of the response

surrogate

The Surrogate for the loss-function

par

Vector of regime parameters

kernel

The Kernel defining the decision function