CenBAR {CenBAR}

Broken Adaptive Ridge Estimator for Censored Data in AFT Model

Description

Prints 'Broken adaptive ridge (BAR) method to the semi-parametric accelerated failure time (AFT) model for right-censored survival data by applying the Leurgan's synthetic data.'.

Usage

CenBAR(X,Y,delta,lambda.path=NULL, enableScreening=FALSE)

Arguments

X

input matrix, of dimension nobs x nvars; each row is an observation vector.

Y

response variable.

delta

The status indicator, normally 0=alive, 1=dead.

lambda.path

A user supplied lambda sequence. One usage is to have the program compute its own lambda sequence based on nlambda and lambdaMax. lamdMax = max((t(x)*Y)^2/(4*t(x)*x)). The other usage is use the sequence depend on user's data.

enableScreening

If nobs > nvars, there is no need to do screening; If nobs <= nvars, it will do variable screening and then variable selection and estimate (defalt is FALSE).

Value

beta

the coefficients estimation of the variables.

Author(s)

Zhihua Sun, Chunyu Yu

Examples

  X=matrix(rnorm(10*2),10,2)
  Y=abs(rnorm(10))
  delta=sample(0:1,10,replace=TRUE)
  lambda.path <- seq(0.1, 10, l=5)
  fit = CenBAR(X,Y,delta,lambda.path)