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May 1997 An almost sure invariance principle for stochastic approximation procedures in linear filtering theory
Erich Berger
Ann. Appl. Probab. 7(2): 444-459 (May 1997). DOI: 10.1214/aoap/1034625339

Abstract

In this paper we consider a class of stochastic approximation procedures that arises in linear filtering and regression theory. Our main result asserts that the stochastic approximation process satisfies an almost sure invariance principle (with a certain rate of convergence) if the partial sums of the errors do.

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Erich Berger. "An almost sure invariance principle for stochastic approximation procedures in linear filtering theory." Ann. Appl. Probab. 7 (2) 444 - 459, May 1997. https://doi.org/10.1214/aoap/1034625339

Information

Published: May 1997
First available in Project Euclid: 14 October 2002

zbMATH: 0877.62078
MathSciNet: MR1442321
Digital Object Identifier: 10.1214/aoap/1034625339

Subjects:
Primary: 62L20
Secondary: 60F17 , 62M20

Keywords: almost sure invariance principles , linear filtering , stochastic approximation

Rights: Copyright © 1997 Institute of Mathematical Statistics

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Vol.7 • No. 2 • May 1997
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