This book provides a self-contained presentation on the structure of a large class of stable processes, known as self-similar mixed moving averages. The authors present a way to describe and classify these processes by relating them to so-called deterministic flows. The first sections in the book review random variables, stochastic processes, and integrals, moving on to rigidity and flows, and finally ending with mixed moving averages and self-similarity. In-depth appendices are also included. This book is aimed at ...
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This book provides a self-contained presentation on the structure of a large class of stable processes, known as self-similar mixed moving averages. The authors present a way to describe and classify these processes by relating them to so-called deterministic flows. The first sections in the book review random variables, stochastic processes, and integrals, moving on to rigidity and flows, and finally ending with mixed moving averages and self-similarity. In-depth appendices are also included. This book is aimed at graduate students and researchers working in probability theory and statistics.
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Add this copy of Stable Non-Gaussian Self-Similar Processes with to cart. $51.65, new condition, Sold by Ingram Customer Returns Center rated 5.0 out of 5 stars, ships from NV, USA, published 2017 by Springer.
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New. Trade paperback (US). Glued binding. 135 p. Contains: Unspecified, Illustrations, black & white. Springerbriefs in Probability and Mathematical Statistics.
Add this copy of Stable Non-Gaussian Self-Similar Processes with to cart. $53.66, new condition, Sold by Booksplease rated 4.0 out of 5 stars, ships from Southport, MERSEYSIDE, UNITED KINGDOM, published 2017 by Springer.
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New. Trade paperback (US). Glued binding. 135 p. Contains: Unspecified, Illustrations, black & white. Springerbriefs in Probability and Mathematical Statistics.
