HR: Estimator of the hazard rate function by a kernel method
In EstSimPDMP: Estimation and Simulation for PDMPs

Description Usage Arguments Author(s) References See Also Examples

The function computes the estimator of the hazard rate function from positive data. This is the smoothed estimator given in the article written by Ramlau-Hansen. The kernel must be continuous with support [-1,1]. The chosen kernel is the Epanechnikov kernel.

1	HR(dat,t,h,alpha,bound)

`dat`	data from which the estimator is to be computed.
`t`	the estimator is computed at time t.
`h`	bandwith
`alpha`	strictly positive real number. If h is NULL, the bandwith is 1/n^alpha where n is the number of data.
`bound`	the estimator is computed as an integral between the times 0 and bound. bound may be the deterministic time of censorship. The default value is Inf: it means that there is no censorship.

Romain Azais

Ramlau-Hansen H. Smoothing counting process intensities by means of kernel functions The Annals of Statistics, Vol. 11, No.2, (1983) 453-466

Andersen P.K., Borgan O., Gill R.D., Keiding N. Statistical models based on counting processes Springer Series in Statistics. Springer-Verlag, New-York (1993)

CHR, plotHR

# HR

# Simulation of 50 independent exponential random variables
dat<-rexp(50,1)

# Estimation of the exponential hazard rate at time 0.4
HR(dat,0.4)