R: Fits Krylow based PLS for additive hazards model

krylow.pls {timereg} | R Documentation

## Fits Krylow based PLS for additive hazards model

### Description

Fits the PLS estimator for the additive risk model based on the least squares fitting criterion

### Usage

    krylow.pls(D, d, dim = 1)

### Arguments

`D` | defined above
`d` | defined above
`dim` | number of pls dimensions

### Details

L(β,D,d) = β^T D β - 2 β^T d

where D=\int Z H Z dt and d=\int Z H dN.

### Value

returns a list with the following arguments:

`beta` | PLS regression coefficients

### Author(s)

Thomas Scheike

### References

Martinussen and Scheike, The Aalen additive hazards model with high-dimensional regressors, submitted.

Martinussen and Scheike, Dynamic Regression Models for Survival Data, Springer (2006).

### Examples

    ## makes data for pbc complete case
    data(mypbc)
    pbc<-mypbc
    pbc$time<-pbc$time+runif(418)*0.1; pbc$time<-pbc$time/365
    pbc<-subset(pbc,complete.cases(pbc));
    covs<-as.matrix(pbc[,-c(1:3,6)])
    covs<-cbind(covs[,c(1:6,16)],log(covs[,7:15]))

    ## computes the matrices needed for the least squares
    ## criterion
    out<-aalen(Surv(time,status>=1)~const(covs),pbc,robust=0,n.sim=0)
    S=out$intZHZ; s=out$intZHdN;

    out<-krylow.pls(S,s,dim=2)

[Package timereg version 1.9.4 Index]