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Limit Distributions for Sums of Independent Random Vectors: Heavy Tails in Theory and Practice - Hardcover
Synopsis
A comprehensive introduction to the central limit theory-from foundations to current research
This volume provides an introduction to the central limit theory of random vectors, which lies at the heart of probability and statistics. The authors develop the central limit theory in detail, starting with the basic constructions of modern probability theory, then developing the fundamental tools of infinitely divisible distributions and regular variation. They provide a number of extensions and applications to probability and statistics, and take the reader through the fundamentals to the current level of research.
In synthesizing results from nearly 200 research papers and presenting them in a self-contained form, authors Meerschaert and Scheffler have produced an accessible reference that treats the central limit theory honestly and focuses on multivariate models. For researchers, it provides an efficient and logical path through a large collection of results with many possible applications to real-world phenomena. Limit Distributions for Sums of Independent Random Vectors includes a coherent introduction to limit distributions and these other features:
* A self-contained introduction to the multivariate problem
* Multivariate regular variation for linear operators, real-valued functions, and Borel Measures
* Multivariate limit theorems: limit distributions, central limit theorems, and related limit theorems
* Real-world applications
Limit Distributions for Sums of Independent Random Vectors is a comprehensive reference that provides an up-to-date survey of the state of the art in this important research area.
"synopsis" may belong to another edition of this title.
About the Author
MARK M. MEERSCHAERT, PhD, is Associate Professor of Mathematics at the University of Nevada-Reno. He is also the author of Mathematical Modeling.
HANS-PETER SCHEFFLER, PhD, is Associate Professor of Mathematics at the University of Dortmund, Germany.
From the Back Cover
A comprehensive introduction to the central limit theory-from foundations to current research
This volume provides an introduction to the central limit theory of random vectors, which lies at the heart of probability and statistics. The authors develop the central limit theory in detail, starting with the basic constructions of modern probability theory, then developing the fundamental tools of infinitely divisible distributions and regular variation. They provide a number of extensions and applications to probability and statistics, and take the reader through the fundamentals to the current level of research.
In synthesizing results from nearly 200 research papers and presenting them in a self-contained form, authors Meerschaert and Scheffler have produced an accessible reference that treats the central limit theory honestly and focuses on multivariate models. For researchers, it provides an efficient and logical path through a large collection of results with many possible applications to real-world phenomena. Limit Distributions for Sums of Independent Random Vectors includes a coherent introduction to limit distributions and these other features:
* A self-contained introduction to the multivariate problem
* Multivariate regular variation for linear operators, real-valued functions, and Borel Measures
* Multivariate limit theorems: limit distributions, central limit theorems, and related limit theorems
* Real-world applications
Limit Distributions for Sums of Independent Random Vectors is a comprehensive reference that provides an up-to-date survey of the state of the art in this important research area.
From the Inside Flap
A comprehensive introduction to the central limit theory-from foundations to current research
This volume provides an introduction to the central limit theory of random vectors, which lies at the heart of probability and statistics. The authors develop the central limit theory in detail, starting with the basic constructions of modern probability theory, then developing the fundamental tools of infinitely divisible distributions and regular variation. They provide a number of extensions and applications to probability and statistics, and take the reader through the fundamentals to the current level of research.
In synthesizing results from nearly 200 research papers and presenting them in a self-contained form, authors Meerschaert and Scheffler have produced an accessible reference that treats the central limit theory honestly and focuses on multivariate models. For researchers, it provides an efficient and logical path through a large collection of results with many possible applications to real-world phenomena. Limit Distributions for Sums of Independent Random Vectors includes a coherent introduction to limit distributions and these other features:
* A self-contained introduction to the multivariate problem
* Multivariate regular variation for linear operators, real-valued functions, and Borel Measures
* Multivariate limit theorems: limit distributions, central limit theorems, and related limit theorems
* Real-world applications
Limit Distributions for Sums of Independent Random Vectors is a comprehensive reference that provides an up-to-date survey of the state of the art in this important research area.
"About this title" may belong to another edition of this title.
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Limit Distributions for Sums of Independent Random Vectors (Hardcover)
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John Wiley & Sons Inc, New York, 2001
ISBN 10: 0471356298
ISBN 13: 9780471356295
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Hardcover. Condition: new. Hardcover. A comprehensive introduction to the central limit theory-from foundations to current research This volume provides an introduction to the central limit theory of random vectors, which lies at the heart of probability and statistics. The authors develop the central limit theory in detail, starting with the basic constructions of modern probability theory, then developing the fundamental tools of infinitely divisible distributions and regular variation. They provide a number of extensions and applications to probability and statistics, and take the reader through the fundamentals to the current level of research. In synthesizing results from nearly 200 research papers and presenting them in a self-contained form, authors Meerschaert and Scheffler have produced an accessible reference that treats the central limit theory honestly and focuses on multivariate models. For researchers, it provides an efficient and logical path through a large collection of results with many possible applications to real-world phenomena. Limit Distributions for Sums of Independent Random Vectors includes a coherent introduction to limit distributions and these other features: * A self-contained introduction to the multivariate problem * Multivariate regular variation for linear operators, real-valued functions, and Borel Measures * Multivariate limit theorems: limit distributions, central limit theorems, and related limit theorems * Real-world applications Limit Distributions for Sums of Independent Random Vectors is a comprehensive reference that provides an up-to-date survey of the state of the art in this important research area. This book provides an accessible, serious, and multivariate introduction to the central limit theorem of random variables that lies at the heart of probability and statistics. Practical applications of stable random variables are showcased. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9780471356295
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Limit Distributions for Sums of Independent Random Vectors (Hardcover)
Published by
John Wiley & Sons Inc, New York, 2001
ISBN 10: 0471356298
ISBN 13: 9780471356295
New
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First Edition
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Hardcover. Condition: new. Hardcover. A comprehensive introduction to the central limit theory-from foundations to current research This volume provides an introduction to the central limit theory of random vectors, which lies at the heart of probability and statistics. The authors develop the central limit theory in detail, starting with the basic constructions of modern probability theory, then developing the fundamental tools of infinitely divisible distributions and regular variation. They provide a number of extensions and applications to probability and statistics, and take the reader through the fundamentals to the current level of research. In synthesizing results from nearly 200 research papers and presenting them in a self-contained form, authors Meerschaert and Scheffler have produced an accessible reference that treats the central limit theory honestly and focuses on multivariate models. For researchers, it provides an efficient and logical path through a large collection of results with many possible applications to real-world phenomena. Limit Distributions for Sums of Independent Random Vectors includes a coherent introduction to limit distributions and these other features: * A self-contained introduction to the multivariate problem * Multivariate regular variation for linear operators, real-valued functions, and Borel Measures * Multivariate limit theorems: limit distributions, central limit theorems, and related limit theorems * Real-world applications Limit Distributions for Sums of Independent Random Vectors is a comprehensive reference that provides an up-to-date survey of the state of the art in this important research area. This book provides an accessible, serious, and multivariate introduction to the central limit theorem of random variables that lies at the heart of probability and statistics. Practical applications of stable random variables are showcased. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9780471356295
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