Self-Normalized Processes: Limit Theory and Statistical Applications - Qi-Man Shao,Victor H. Peña,Tze Leung Lai
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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 applic ... Full description
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Description
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.
More Information
| Author | Qi-Man Shao, Victor H. Peña, Tze Leung Lai |
|---|---|
| Publisher | Springer Berlin Heidelberg |
| Series | Probability and Its Applications |
| Release year | 2010 |
| Cover type | Softcover |
| EAN | 9783642099267 |