coxgrad.RdCompute the gradient of the partial likelihood at a particular fit
coxgrad(f, time, d, w, eps = 1e-05)
| 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 |
a single gradient vector the same length as f
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
coxnet.deviance