Kernel density estimation and goodness-of-fit test in adaptive tracking
BERCU, Bernard
Laboratoire de Statistique et Probabilités [LSP]
Quality control and dynamic reliability [CQFD]
Laboratoire de Statistique et Probabilités [LSP]
Quality control and dynamic reliability [CQFD]
BERCU, Bernard
Laboratoire de Statistique et Probabilités [LSP]
Quality control and dynamic reliability [CQFD]
< Reduce
Laboratoire de Statistique et Probabilités [LSP]
Quality control and dynamic reliability [CQFD]
Language
en
Article de revue
This item was published in
SIAM Journal on Control and Optimization. 2008, vol. 47, p. 2440-2457
Society for Industrial and Applied Mathematics
English Abstract
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 ...Read more >
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.Read less <
English Keywords
Adaptive control
Kernel density estimation
Goodness-of-fit test
Origin
Hal imported