internal-owl-class: Class '.owl'

Description Slots

Description

Class .owl stores parameters required for OWL optimization step

Slots

x

Matrix of covariates for kernel

txSignR

Vector of tx multiplied by the sign of the response

txVec

Vector of tx coded as -1/1

absRinvPi

Vector of the absolute value of the response weighted by the propensity for the tx received

response

Vector of the response

invPi

Vector of the inverse of the propensity for the tx received

surrogate

The Surrogate for the loss-function

pars

Vector of regime parameters

kernel

The Kernel defining the decision function


DynTxRegime documentation built on Nov. 10, 2020, 1:08 a.m.