Self-Normalized Processes: Limit Theory and Statistical Applications

di Victor H. Peña (Autore)

Tze Leung Lai (Autore)

Qi-Man Shao (Autore)

Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, 2010

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.

• Autore: Victor H. Peña, Tze Leung Lai, Qi-Man Shao
• Editore: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
• Collana: Probability and Its Applications
• Anno: 2010
• Rilegatura: Paperback / softback
• Pagine: 275 p.
• Dimensioni: 235 x 155 mm
• EAN: 9783642099267

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