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Limit theorems for stochastic approximation algorithms.

Renlund, Henrik, 1979- (author)
Uppsala universitet,Matematisk statistik
 (creator_code:org_t)
2011
English 26 s.
Series: U.U.D.M ; 2011:6
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  • 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.

Subject headings

NATURVETENSKAP  -- Matematik -- Sannolikhetsteori och statistik (hsv//swe)
NATURAL SCIENCES  -- Mathematics -- Probability Theory and Statistics (hsv//eng)

Keyword

stochastic approximation algorithms
central limit theorem
generalized Polya urn
Mathematical statistics
Matematisk statistik
Mathematical Statistics
Matematisk statistik

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