# epa: Excess hazard function smoothing In relsurv: Relative Survival

 epa R Documentation

## Excess hazard function smoothing

### Description

An Epanechnikov kernel function based smoother for smoothing the baseline excess hazard calculated by the `rsadd` function with the `EM` method.

### Usage

```epa(fit,bwin,times,n.bwin=16,left=FALSE)
```

### Arguments

 `fit` Fit from the additive relative survival model using the `EM` method. `bwin` The relative width of the smoothing window (default is 1). `times` The times at which the smoother is to be evaluated. If missing, it is evaluated at all event times. `n.bwin` Number of times that the window width may change. `left` If `FALSE` (default) smoothing is performed symmetrically, if `TRUE` only leftside neighbours are considered.

### Details

The function performs Epanechnikov kernel smoothing. The follow up time is divided (according to percentiles of event times) into several intervals (number of intervals defined by `n.bwin`) in which the width is calculated as a factor of the maximum span between event times. Boundary effects are also taken into account on both sides.

### Value

A list with two components:

 `lambda` the smoothed excess baseline hazard function `times` the times at which the smoothed excess baseline hazard is evaluated.

### References

Package. Pohar M., Stare J. (2006) "Relative survival analysis in R." Computer Methods and Programs in Biomedicine, 81: 272–278

Relative survival: Pohar, M., Stare, J. (2007) "Making relative survival analysis relatively easy." Computers in biology and medicine, 37: 1741–1749.

EM algorithm: Pohar Perme M., Henderson R., Stare, J. (2009) "An approach to estimation in relative survival regression." Biostatistics, 10: 136–146.

`rsadd`,

### Examples

```data(slopop)
data(rdata)
#fit an additive model with the EM method