Abstract
A smoothing parameter inversely proportional to the square root of the true density is known to produce kernel estimates of the density having faster bias rate of convergence. We show that in the case of kernel-based nonparametric hazard rate estimation, a smoothing parameter inversely proportional to the square root of the true hazard rate leads to a mean square error rate of order n-8/9, an improvement over the standard second order kernel. An adaptive version of such a procedure is considered and analyzed.
Original language | English |
---|---|
Pages (from-to) | 1055-1078 |
Number of pages | 24 |
Journal | Communications in Statistics: Theory and Methods |
Volume | 38 |
Issue number | 7 |
DOIs | |
Publication status | Published - 1 Jan 2009 |
Keywords
- Smoothness
- Variable bandwidth
- Mean integrated square error
- Kernel
- Hazard rate estimation