Self-Normalized Processes
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<P>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.</P><P>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.</P>
![Self-Normalized Processes Self-Normalized Processes](https://cos.richshop.de/servlet/images/9783540856368.jpg?w=300)
- Autor: Tze Leung Lai / Victor H. Peña / Qi-Man Shao
- Seitenzahl: 275
- Format: PDF
- DRM: social-drm (ohne Kopierschutz)
- Erscheinungsdatum: 25.12.2008
- Herausgeber: SPRINGER