Self-Normalized Processes: Limit Theory and Statistical Applications

byVictor H. Pe, Tze Leung Lai, Qi-Man Shao

Paperback | November 30, 2010

Self-Normalized Processes: Limit Theory and Statistical Applications by Victor H. Pe
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Self-normalized processes are of common occurrence in probabilistic and statistical studies. A prototypical example is Student's t-statistic introduced in 1908 by Gosset, whose portrait is on the front cover. Due to the highly non-linear nature of these processes, the theory experienced a long period of slow development. In recent years there have been a number of important advances in the theory and applications of self-normalized processes. Some of these developments are closely linked to the study of central limit theorems, which imply that self-normalized processes are approximate pivots for statistical inference.

The present volume covers recent developments in the area, including self-normalized large and moderate deviations, and laws of the iterated logarithms for self-normalized martingales. This is the first book that systematically treats the theory and applications of self-normalization.

Victor H. de la Peña is Fellow of Institute of Mathematical Statistics and a Medallion Lecturer for IMS in 2007.Tze Leung LAI: Distinguished Lecture Series in Statistical Science from Academia Sinica (2001), Starr Lectures in Financial Mathematics from the University of Hong Kong (2001), Center for Advanced Study in the Behavioral Scie...
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Title:Self-Normalized Processes: Limit Theory and Statistical ApplicationsFormat:PaperbackProduct dimensions:275 pages, 9.25 X 6.1 X 0 inShipping dimensions:275 pages, 9.25 X 6.1 X 0 inPublished:November 30, 2010Publisher:Springer-Verlag/Sci-Tech/TradeLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:3642099262

ISBN - 13:9783642099267

Appropriate for ages: All ages

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