tlp_S_VS: Cost function in psi-Learn with variable selection

Description Usage Arguments Value Author(s)

View source: R/InitialEst.R

Description

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

Usage

1
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 <[email protected]>


mylzwq/psi-learning-for-ITR documentation built on Sept. 23, 2018, 12:56 a.m.