A note on smoothed estimating functions |
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| Authors: | A. Thavaneswaran and Jagbir Singh |
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| Affiliation: | (1) Department of Statistics, University of Manitoba, R3T 2N2 Winnipeg, Canada;(2) Department of Statistics, Temple University, 19122 Philadelphia, PA, USA |
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| Abstract: | The kernel estimate of regression function in likelihood based models has been studied in Staniswalis (1989,J. Amer. Statist. Assoc.,84, 276–283). The notion of optimal estimation for the nonparametric kernel estimation of semimartingale intensity  (t) is proposed. The goal is to arrive at a nonparametric estimate of  0=(t0) for a fixed pointt0  [0, 1]. We consider the estimator that is a solution of the smoothed optimal estimating equation is the optimal estimating function as in Thavaneswaran and Thompson (1986,J. Appl. Probab.,23, 409–417). |
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| Keywords: | Censored observations semimartingales optimal estimation smoothing |
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