Adaptive deadband control of a drifting process with unknown parameters

Adjusting a drifting process to minimize the expected sum of quadratic off-target and fixed adjustment costs is considered under unknown process parameters. A Bayesian approach based on sequential Monte Carlo methods is presented. The benefits of the resulting "deadband" adjustment policy are studied.

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Year of publication:	2007
Authors:	Lian, Zilong ; del Castillo, Enrique
Published in:	Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 77.2007, 8, p. 843-852
Publisher:	Elsevier
Keywords:	Fixed adjustment cost Sequential Monte Carlo methods Random walk Bounded adjustment

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005137684