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Limit theorems for stochastic approximation algorithms.
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Mathematics, Mathematical Statistics.
2011 (English)Report (Other academic)
Abstract [en]

We prove a central limit theorem applicable to one dimensional stochastic approximation algorithms that converge to a point where the error terms of the algorithm do not vanish. We show how this applies to a certain class of these algorithms that in particular covers a generalized Pólya urn model, which is also discussed.  In addition, we  show how to scale these algorithms in some cases where we cannot determine the limiting distribution but expect it to be non-normal.

Place, publisher, year, edition, pages
2011. , 26 p.
, U.U.D.M, 2011:6
Keyword [en]
stochastic approximation algorithms, central limit theorem, generalized Polya urn
National Category
Probability Theory and Statistics
Research subject
Mathematical Statistics
URN: urn:nbn:se:uu:diva-145343OAI: oai:DiVA.org:uu-145343DiVA: diva2:396177
Available from: 2011-02-09 Created: 2011-02-08 Last updated: 2011-02-14Bibliographically approved

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Renlund, Henrik
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