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 chapter of the book is supplemented by numerous exercises, some designed to test the reader's understanding, while others invite the reader to consider some of the open research problems in the field today.
See more
Current price
€93.09
Original price
€97.99
Save 5%
Delivery/Collection within 10-20 working days
Product Details
Weight: 1420g
Dimensions: 182 x 260mm
Publication Date: 18 Apr 2017
Publisher: Cambridge University Press
Publication City/Country: United Kingdom
Language: English
ISBN13: 9781107039469
About Murad S. TaqquVladas Pipiras
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 with applications in econometrics neuroscience engineering computer science and other areas. He has written over fifty research papers and is coauthor of A Basic Course in Measure and Probability: Theory for Applications (with Ross Leadbetter and Stamatis Cambanis Cambridge 2014) Murad S. Taqqu's research involves self-similar processes their connection to time series with long-range dependence the development of statistical tests and the study of non-Gaussian processes whose marginal distributions have heavy tails. He has written more than 250 scientific papers and is coauthor of Stable Non-Gaussian Random Processes (with Gennady Samorodnitsky 1994). Professor Taqqu is a Fellow of the Institute of Mathematical Statistics and has been elected Member of the International Statistical Institute. He has received a number of awards including a John Simon Guggenheim Fellowship the 1995 William J. Bennett Award the 1996 Institute of Electrical and Electronics Engineers W. R. G. Baker Prize the 2002 EURASIP Best Paper in Signal Processing Award and the 2006 Association for Computing Machinery Special Interest Group on Data Communications (ACM SIGCOMM) Test of Time Award.