R: Baseline hazard function

basehaz.gbm {gbm} | R Documentation

## Baseline hazard function

### Description

Computes the Breslow estimator of the baseline hazard function for a proportional hazard regression model

### Usage

    basehaz.gbm(t, delta, f.x,
                t.eval = NULL,
                smooth = FALSE,
                cumulative = TRUE)

### Arguments

`t` | the survival times
`delta` | the censoring indicator
`f.x` | the predicted values of the regression model on the log hazard scale
`t.eval` | values at which the baseline hazard will be evaluated
`smooth` | if `TRUE` `basehaz.gbm` will smooth the estimated baseline hazard using Friedman's super smoother `supsmu`
`cumulative` | if `TRUE` the cumulative survival function will be computed

### Details

The proportional hazard model assumes h(t|x)=lambda(t)*exp(f(x)). `gbm` can estimate the f(x) component via partial likelihood. After estimating f(x), `basehaz.gbm` can compute the a nonparametric estimate of lambda(t).

### Value

a vector of length equal to the length of t (or of length `t.eval` if `t.eval` is not `NULL`) containing the baseline hazard evaluated at t (or at `t.eval` if `t.eval` is not `NULL`). If `cumulative` is set to `TRUE` then the returned vector evaluates the cumulative hazard function at those values.

### Author(s)

Greg Ridgeway gregridgeway@gmail.com

### References

N. Breslow (1972). "Disussion of ‘Regression Models and Life-Tables’ by D.R. Cox," Journal of the Royal Statistical Society, Series B, 34(2):216-217.

N. Breslow (1974). "Covariance analysis of censored survival data," Biometrics 30:89-99.

### See Also

`survfit`, `gbm`

[Package gbm version 2.1.3 Index]