tlp_S_VS: Cost function in psi-Learn with variable selection

In mylzwq/psi-learning-for-ITR: An Implementation of psiLearn on Individualized Treatment Rule

Description

calculate the cost in psi-Learn with ridge penalty and TLP penalty

Usage

tlp_S_VS(X,A,R,wt,w,tau=0.1,kappa=0.1,lambda=0.1,tau2=0.1,kernel='linear')

Arguments

X	n by p input matrix.
A	a vector of n entries coded 1 and -1 for the treatment assignments.
R	a vector of outcome variable, larger is more desirable.
wt	a vector of weights for each observation.
w	coefficients for the decision function, the first element is the bias
tau	tuning parameter for the loss function in psi-Learn
kappa	tunning parameter to control the complexity of the decision function in the ridge penaly
lambda	tunning parameter to control the complexity of the decision function in the TLP penalty
tau2	tunning parameter to control in margin in the TLP penalty
kernel	kernel function for pai-Learn, can be 'linear' or 'rbf' (radial basis kernel), default is 'linear'.

Value

It returns the cost value in psi-Learn

cost	the cost value in psi-Learn

Author(s)

MingyangLiu <[e-mail]>

mylzwq/psi-learning-for-ITR documentation built on May 15, 2019, 1:18 p.m.