Kernel Density Estimation and Goodness-of-Fit Test in Adaptive Tracking
نویسندگان
چکیده
We investigate the asymptotic properties of a recursive kernel density estimator associated with the driven noise of a linear regression in adaptive tracking. We provide an almost sure pointwise and uniform strong law of large numbers as well as a pointwise and multivariate central limit theorem. We also propose a goodness-of-fit test together with some simulation experiments.
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ورودعنوان ژورنال:
- SIAM J. Control and Optimization
دوره 47 شماره
صفحات -
تاریخ انتشار 2008