Wavelet Analysis of Change Points in Nonparametric Hazard Rate Models Under Random Censorship

Abstract

In this article, we consider detection and estimation of change points in nonparametric hazard rate models. Wavelet methods are utilized to develop a testing procedure for change points detection. The asymptotic properties of the test statistic are explored. When there exist change points in hazard function, we also propose estimators for the number, the locations, and the jump sizes of the change points. The asymptotic properties of these estimators are systematically derived. Some simulation examples are conducted to assess the finite sample performance of the proposed approach and to make comparisons with some existing methods. A real data analysis is provided to illustrate the new approach.

Keywords:

• Change points
• Random censoring
• Counting process
• Wavelet coefficient
• Kernel estimation.

Mathematics Subject Classification:

• Primary 62G10
• Secondary 62N02
• 62N03.