Truncated stochastic approximation with moving bounds: convergence

In this paper we consider a wide class of truncated stochastic approximation procedures. These procedures have three main characteristics: truncations with random moving bounds, a matrix valued random step-size sequence, and a dynamically changing random regression function. We establish convergence and consider several examples to illustrate the results. Copyright Springer Science+Business Media Dordrecht 2014

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Year of publication:	2014
Authors:	Sharia, Teo
Published in:	Statistical Inference for Stochastic Processes. - Springer. - Vol. 17.2014, 2, p. 163-179
Publisher:	Springer
Subject:	Stochastic approximation \| Recursive estimation \| Parameter estimation

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Extent:	text/html
Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://ebvufind01.dmz1.zbw.eu/10010793919