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 α(t) is proposed. The goal is to arrive at a nonparametric estimate\(\hat \theta _0 \) of ϑ0=α(t 0) for a fixed pointt 0 ∈ [0, 1]. We consider the estimator that is a solution of the smoothed optimal estimating equation\(\hat \theta _0 \) is the optimal estimating function as in Thavaneswaran and Thompson (1986,J. Appl. Probab.,23, 409–417).
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Thavaneswaran, A., Singh, J. A note on smoothed estimating functions. Ann Inst Stat Math 45, 721–729 (1993). https://doi.org/10.1007/BF00774783
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DOI: https://doi.org/10.1007/BF00774783