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Springer Self-Normalized Processes: Limit Theory and Statistical Applications (Probability and Its Applications)
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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.
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Product Specifications
- Brand
- Springer
- Format
- hardcover
- ASIN
- 3540856358
- Domain
- Amazon UK
- Release Date
- 28 January 2009
- Listed Since
- 04 August 2008
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