R: compute gradient for cox model

coxgrad {glmnet} | R Documentation

## compute gradient for cox model

### Description

Compute the gradient of the partial likelihood at a particular fit

### Usage

    coxgrad(f, time, d, w, eps = 1e-05)

### Arguments

`f` | fit vector
`time` | time vector (can have ties)
`d` | death/censoring indicator 1/0
`w` | observation weights (default equal)
`eps` | (default 0.00001) Breaks ties between death and censoring by making death times `eps` earlier

### Details

Compute a gradient vector at the fitted vector for the log partial likelihood. This is like a residual vector, and useful for manual screening of predictors for `glmnet` in applications where `p` is very large (as in GWAS). Uses the Breslow approach to ties

### Value

a single gradient vector the same length as `f`

### Author(s)

Trevor Hastie
Maintainer: Trevor Hastie hastie@stanford.edu

### See Also

`coxnet.deviance`

[Package glmnet version 4.0-2 Index]