# coxgrad

From glmnet v3.0-2
by Trevor Hastie

##### compute gradient for cox model

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`

##### See Also

`coxnet.deviance`

*Documentation reproduced from package glmnet, version 3.0-2, License: GPL-2*

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