Kernel Density Estimation and Goodness-of-Fit Test in Adaptive Tracking

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. Key words. Adaptive control, Kernel density estimation, Goodness-of-fit test AMS subject classifications. 93C40, 62G07, 62G10

• Type: Journal
• Year: 2008
• Where: SIAMCO
• Authors: Bernard Bercu, Bruno Portier
• Keywords: Kernel Density, Kernel Density Estimator, SIAMCO 2008, Sure Pointwise