| SDHazardRateEst {NPHazardRate} | R Documentation |
Kernel Second Derivative Hazard Rate Estimation
Description
Implements the kernel estimate of the second derivative of the hazard rate for right censored data defined - based on the estimate of Tanner and Wong (1983). The implementation is based on the second derivative of the Biweight Kernel.
Usage
SDHazardRateEst(xin, xout, h, ci)
Arguments
xin |
A vector of data points. Missing values not allowed. |
xout |
A vector of grid points at which the estimates will be calculated. |
h |
A scalar, the bandwidth to use in the estimate. |
ci |
A vector of censoring indicators: 1's indicate uncensored observations, 0's correspond to censored obs. |
Details
The function SDHazardRateEst implements the kernel estimate of the second derivative of the hazard rate estimator, given by
\hat \lambda_2(x;h) = \sum_{i=1}^n \frac{K_h''(x-X_{(i)})\delta_{(i)}}{n-i+1}
where K is taken to be the Biweight kernel. The function is used for estimation of the functional R(\lambda'') in PlugInBand so a default bandwidth rule is used for h provided in (16), Hua, Patil and Bagkavos (2018).
Value
A vector with the second derivative of the hazard rate at the designated points xout.