Univariate Stable Distributions: Models for Heavy Tailed Data

Name: Univariate Stable Distributions: Models for Heavy Tailed Data
Brand: Springer Verlag
SKU: 9783030529178
Price: 3526.0 INR
Availability: InStock

by Nolan , John P.

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ISBN13: 9783030529178
Binding: Paperback
Subject: Mathematics and Statistics
Publisher: Springer Verlag
Publisher Imprint: Springer
Publication Date: January 1, 2021
Pages: 333
Original Price: EUR 49.99
Language: English
Edition: N/A
Item Weight: 638 grams
BISAC Subject(s): Probability & Statistics / General and Applied

About The Book

From the Back Cover
This textbook highlights the many practical uses of stable distributions, exploring the theory, numerical algorithms, and statistical methods used to work with stable laws. Because of the author's accessible and comprehensive approach, readers will be able to understand and use these methods. Both mathematicians and non-mathematicians will find this a valuable resource for more accurately modelling and predicting large values in a number of real-world scenarios.
Beginning with an introductory chapter that explains key ideas about stable laws, readers will be prepared for the more advanced topics that appear later. The following chapters present the theory of stable distributions, a wide range of applications, and statistical methods, with the final chapters focusing on regression, signal processing, and related distributions. Each chapter ends with a number of carefully chosen exercises. Links to free software are included as well, where readers can put these methods into practice.
Univariate Stable Distributions is ideal for advanced undergraduate or graduate students in mathematics, as well as many other fields, such as statistics, economics, engineering, physics, and more. It will also appeal to researchers in probability theory who seek an authoritative reference on stable distributions.

About The Author

John Nolan received his PhD from the University of Virginia, and has taught at the University of Zambia, Kenyon College, and American University. He also worked in a software firm, developing systems for intensive care units. His main research interests are in models for heavy tailed data and extremes.

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