Stable Non-Gaussian Random Processes: Stochastic Models with Infinite Variance (Stochastic Modeling, Band 1) - Hardcover

Buch 1 von 2: Stochastic Modeling Series

Samorodnitsky, Gennady; Taqqu, M. S.

 
9780412051715: Stable Non-Gaussian Random Processes: Stochastic Models with Infinite Variance (Stochastic Modeling, Band 1)
Hardcover
ISBN 10: 0412051710 ISBN 13: 9780412051715
Verlag: Taylor & Francis Ltd, 1994

Inhaltsangabe

This book presents similarity between Gaussian and non-Gaussian stable multivariate distributions and introduces the one-dimensional stable random variables. It discusses the most basic sample path properties of stable processes, namely sample boundedness and continuity.

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Über die Autorin bzw. den Autor

Samoradnitsky, Gennady

Von der hinteren Coverseite

The familiar Gaussian models do not allow for large deviations and are thus often inadequate for modeling high variability. Non-Gaussian stable models do not possess such limitations. They all share a familiar feature which differentiates them from the Gaussian ones. Their marginal distributions possess heavy "probability tails", always with infinite variance and in some cases with infinite first moment. The aim of this book is to make this exciting material easily accessible to graduate students and practitioners. Assuming only a first-year graduate course in probability, it includes material which has appeared only recently in journals and unpublished materials. Each chapter begins with a brief overview and concludes with a range of exercises at varying levels of difficulty. Proofs are spelled out in detail. The book includes a discussion of self-similar processes, ARMA, and fractional ARIMA time series with stable innovations.

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Verlag
Taylor & Francis Ltd
Erscheinungsdatum
1994
Sprache
Englisch
ISBN 10 
0412051710
ISBN 13 
9780412051715
Einband
Gebundene Ausgabe
Anzahl der Seiten
632
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