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Robust estimation using the Robbins-Monro stochastic approximation algorithm | IEEE Journals & Magazine | IEEE Xplore

Robust estimation using the Robbins-Monro stochastic approximation algorithm


Abstract:

The problem of minmax estimation of a location parameter introduced by Huber is considered. It is shown that under general conditions there exists a solution which is a f...Show More

Abstract:

The problem of minmax estimation of a location parameter introduced by Huber is considered. It is shown that under general conditions there exists a solution which is a form of the Robbins-Monro stochastic approximation algorithm. This generalizes earlier work by Martin and Masreliez who have given stochastic approximation (SA)-estimate solutions for two particular cases. As with theM-estimate solutions given by Huber, the SA solutions are completely determined by the probability distribution function with least Fisher information in the distribution set used to model the observation errors.
Published in: IEEE Transactions on Information Theory ( Volume: 25, Issue: 6, November 1979)
Page(s): 698 - 704
Date of Publication: 06 January 2003

ISSN Information:


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