getfinalSCADcoefCOX: SCAD regularized loglikelihood for Cox proportional hazards regression models

Description

This function gets the final regression coefficients for the SCAD regularized loglikelihood for Cox proportional hazards regression models after applying (I)SIS

Usage

getfinalSCADcoefCOX(x, time, status, method = "efron", pickind, 
folds = NULL, eps0 = 1e-5, tune.method = "AIC", inittype = "NoPen",
detailed = FALSE)

Arguments

an (n * p) matrix of features.

time

an (n) vector of the follow up time for right censored data.

status

an (n) vector of the status indicator, normally 0=alive, 1=dead.

method

indicates how to handle observations that have tied (i.e., identical) survival times. The default "efron" method is generally preferred to the once-popular "breslow" method.

pickind

predictor indice selected by (I)SIS.

folds

fold information for cross validation.

eps0

an effecitve zero.

tune.method

method for tuning regularization parameter.

inittype

inittype specifies the type of initial solution for the one-step SCAD. It can be either NoPen or L1.

detailed

indicates whether detailed information will be provided. Default is FALSE.

Value

An initial solution vector wt.initsoln and final solution (p) vector SCADcoef.

References

Jianqing Fan and Runze Li (2002) Variable Selection for Cox's Proportional Hazards Model and Frailty Model. The Annals of Statistics, 30, 74-99. Hui Zou and Runze Li (2008) One-step Sparse Estimates in Nonconcave Penalized Likelihood Models (with discussion). The Annals of Statistics, 36, 1509-1533

Examples

Run this code

set.seed(0)
n=150
p=200
truerho=0.5
beta <- c(4,4,4,-6*sqrt(2),4/3, rep(0,p-5))

corrmat=diag(rep(1-truerho, p))+matrix(truerho, p, p)
corrmat[,4]=sqrt(truerho)
corrmat[4, ]=sqrt(truerho)
corrmat[4,4]=1
corrmat[,5]=0
corrmat[5,]=0
corrmat[5,5]=1
cholmat=chol(corrmat)

x=matrix(rnorm(p*n, mean=0, sd=1), n, p)
x=x%*%cholmat

myrates <- exp(x%*%beta)

ytrue <- rexp(n, rate = myrates) 
cen <- rexp(n, rate = 0.1 )
time <- pmin(ytrue, cen)
status <- as.numeric(ytrue <= cen)

SIScoef <- getfinalSCADcoefCOX(x = x, time = time, status = status, 
            pickind = 1:5)