psi_Init: Initial value estimate for the psiLearn.

Description Usage Arguments Value Author(s) See Also

View source: R/InitialEst.R

Description

Initial value estimate for both psi-linear,psi-kernel,and psi-linear-VS.

Usage

1
psi_Init(X,A,R,tau=0.1,kappa=seq(0.01,1,length.out=10),sigma=NULL,kernel='linear',lambda=NULL,VS=FALSE)

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.

tau

tuning parameter for the loss function in psi-Learn

kappa

tunning parameter to control the complexity of the decision function, a seq of kappa is set as the default.

sigma

bandwidth parameter when the kernel is 'rbf',if not provided,can be estimated from Sig_est

kernel

kernel function for pai-Learn, can be 'linear' or 'rbf' (radial basis kernel), default is 'linear'. When 'rbf' is specified, one can specify the sigma parameter for radial basis kernel or estimate from Sig_est.

lambda

when using the variable selection method for inital estimate, lambda is regarded as the tunning parameter in controlling the complexity in L1 penalty

VS

wheter to use the variable selection method as the inital estimate,default is FALSE

Value

It returns initial estimated coefficients for psiLearn with the best tuning parameters picked by cross validation.

w

the coefficent for the decision function.

bias

the intercept in both the linear case and the kernel case.

Author(s)

MingyangLiu <[email protected]>

See Also

tlp_S


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