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Pipiras, Vladas; Taqqu, Murad S. - Long-Range Dependence and Self-Similarity - 9781107039469 - V9781107039469
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Long-Range Dependence and Self-Similarity

€ 97.87
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Description for Long-Range Dependence and Self-Similarity hardcover. A hands-on guide to Bayesian models with R, JAGS, Python, and Stan code, for a wide range of astronomical data types. Series: Cambridge Series in Statistical and Probabilistic Mathematics. Num Pages: 382 pages, 58 b/w illus. 8 tables. BIC Classification: PBT. Category: (U) Tertiary Education (US: College). Dimension: 253 x 177. .
This modern and comprehensive guide to long-range dependence and self-similarity starts with rigorous coverage of the basics, then moves on to cover more specialized, up-to-date topics central to current research. These topics concern, but are not limited to, physical models that give rise to long-range dependence and self-similarity; central and non-central limit theorems for long-range dependent series, and the limiting Hermite processes; fractional Brownian motion and its stochastic calculus; several celebrated decompositions of fractional Brownian motion; multidimensional models for long-range dependence and self-similarity; and maximum likelihood estimation methods for long-range dependent time series. Designed for graduate students and researchers, each ... Read more

Product Details

Number of pages
382
Publisher
Cambridge University Press United Kingdom
Format
Hardback
Publication date
2017
Series
Cambridge Series in Statistical and Probabilistic Mathematics
Condition
New
Weight
28g
Number of Pages
688
Place of Publication
Cambridge, United Kingdom
ISBN
9781107039469
SKU
V9781107039469
Shipping Time
Usually ships in 7 to 11 working days
Ref
99-6

About Pipiras, Vladas; Taqqu, Murad S.
Vladas Pipiras is Professor of Statistics and Operations Research at the University of North Carolina, Chapel Hill. His research focuses on stochastic processes exhibiting long-range dependence, self-similarity, and other scaling phenomena, as well as on stable, extreme-value and other distributions possessing heavy tails. His other current interests include high-dimensional time series, sampling issues for 'big data', and stochastic dynamical systems, ... Read more

Reviews for Long-Range Dependence and Self-Similarity
'This is a marvelous book that brings together both classical background material and the latest research results on long-range dependence. The book is written so that it can be used as a main source by a graduate student, including all the essential proofs. I highly recommend this book.' Mark M. Meerschaert, Michigan State University 'This volume lays a rock-solid foundation ... Read more

Goodreads reviews for Long-Range Dependence and Self-Similarity


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