Integration by parts for point processes and Monte Carlo estimation
نویسندگان
چکیده
We develop an integration by parts technique for point processes, with application to the computation of sensitivities via Monte Carlo simulations in stochastic models with jumps. The method is applied to density estimation and to the construction of a modified kernel estimator which is less sensitive to variations of the bandwidth parameter than standard kernel estimators. Simulations are presented for a random functional of a log-normal renewal process in order to compare the performance of our modified estimator to standard kernel estimators. AMS Classification: 60H07, 65C05, 62G07, 60G55, 60K15.
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