JSM 2003 Online Program

Abstract #301433

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Activity Number:	246
Type:	Contributed
Date/Time:	Tuesday, August 5, 2003 : 10:30 AM to 12:20 PM
Sponsor:	IMS
Abstract - #301433
Title:	Generalized Smoothed Estimation of Semi-martingale Intensity Functions
Author(s):	Jagbir Singh*+ and A. Thavaneswaran
Companies:	Temple University and University of Manitoba
Address:	Dept. of Statistics, Philadelphia, PA, 19122,
Keywords:	censored observations ; semi-martingales ; hazard function ; smoothing
Abstract:	Motivated by Novak's (2000) paper "Generalized Kernel Density Estimator," a class of nonparametric estimators of the intensity function of the semi-martingale processes is considered. That is, instead of the density function, we consider estimation of the intensity function α(t) for the semi-martingale model dX(t) = α(t)Y(t)dt + dM(t), where X(t) and Y(t), t ≥ 0 are observable and M(t) is a martingale process. The proposed class of estimators includes the kernel smoothed estimator of α(t) by Thavaneswaran and Singh (1993). Asymptotic properties of the proposed estimators with censored observations are discussed.

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