Nonparametric conditional hazard rate estimation: A local linear approach

Share/Save/Bookmark

Spierdijk, L. (2008) Nonparametric conditional hazard rate estimation: A local linear approach. Computational Statistics & Data Analysis, 52 (5). pp. 2419-2434. ISSN 0167-9473

[img] PDF
Restricted to UT campus only
: Request a copy
510kB
Abstract:A new nonparametric estimator for the conditional hazard rate is proposed, which is defined as the ratio of local linear estimators for the conditional density and survivor function. The resulting hazard rate estimator is shown to be pointwise consistent and asymptotically normally distributed under appropriate conditions. Furthermore, plug-in bandwidths based on normal and uniform reference distributions and minimizing the asymptotic mean squared error are derived. In terms of the mean squared error the new estimator is highly competitive in comparison to existing estimators for the conditional hazard rate. Moreover, its smoothing parameters are relatively robust to misspecification of the reference distributions, which facilitates bandwidth selection. Additionally, the new hazard rate estimator is conveniently calculated using standard software for local linear regression. The use of the local linear hazard rate is illustrated in an application to kidney transplant data.
Item Type:Article
Faculty:
Electrical Engineering, Mathematics and Computer Science (EEMCS)
Link to this item:http://purl.utwente.nl/publications/62187
Official URL:http://dx.doi.org/10.1016/j.csda.2007.08.007
Export this item as:BibTeX
EndNote
HTML Citation
Reference Manager

 

Repository Staff Only: item control page

Metis ID: 250879