get.pseudodata.cox: Obtain pseudodata based on the Cox's regression model.

In icmm: Empirical Bayes Variable Selection via ICM/M Algorithm

Description

For Cox's regression model, given the current estimates of regression coefficients, working responses and their corresponding weights are obtained.

Usage

get.pseudodata.cox(Y, X, event, beta, time, ntime, sumevent)

Arguments

Y	an (n*1) numeric matrix of time response.
X	an (n*p) numeric design matrix.
event	an (n*1) numeric matrix of status: of status indicator: 0=right censored, 1=event at time.
beta	a (p*1) matrix of regression coefficients.
time	a vector or sorted value of Y.
ntime	length of the vector time.
sumevent	a vector of size ntime where each element is the sum of event where Y is equal to each value in time.

Value

Return a list including elements

z	an (n*1) matrix of working responses
sigma2	an (n*1) matrix of inverse of weights.

Author(s)

Vitara Pungpapong, Min Zhang, Dabao Zhang

Examples

data(simCox)
Y<-as.matrix(simCox[,1])
event<-as.matrix(simCox[,2])
X<-as.matrix(simCox[,-(1:2)])
time<-sort(unique(Y))
ntime<-length(time)
# sum of event_i where y_i =time_k
sumevent<-rep(0, ntime)
for(j in 1:ntime)
{
  sumevent[j]<-sum(event[Y[,1]==time[j]])
}
# Obtain initial values from lasso
data(initbetaCox)
initbeta<-as.matrix(initbetaCox)
# Get Pseudodata
pseudodata<-get.pseudodata.cox(Y, X, event, initbeta, time, ntime, sumevent)
z<-pseudodata$z
sigma<-sqrt(pseudodata$sigma2)

icmm documentation built on May 26, 2021, 9:06 a.m.