Self-Normalized Processes - Limit Theory and Statistical Applications (Paperback, Softcover reprint of hardcover 1st ed. 2009)

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.

General

Imprint:	Springer-Verlag
Country of origin:	Germany
Series:	Probability and Its Applications
Release date:	November 2010
First published:	2009
Authors:	Victor H. Pena • Tze Leung Lai • Qi-Man Shao
Dimensions:	235 x 155 x 15mm (L x W x T)
Format:	Paperback
Pages:	275
Edition:	Softcover reprint of hardcover 1st ed. 2009
ISBN-13:	978-3-642-09926-7
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics Promotions
LSN:	3-642-09926-2
Barcode:	9783642099267

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