Die Quintessenz aus über 100 Originalarbeiten! Ausgehend von den Grundpfeilern der modernen Wahrscheinlichkeitstheorie entwickeln die Autoren dieses in sich geschlossenen, gut verständlich formulierten Bandes die Theorie der unendlich teilbaren Verteilungen und der regulären Variation. Im Anschluss erarbeiten sie die allgemeine Grenzwerttheorie für unabhängige Zufallsvektoren. Dabei achten sie sorgfältig darauf, alle Aspekte in den Kontext der Wahrscheinlichkeitslehre und Statistik zu stellen und bieten dafür eine Fülle von Zusatzinformationen an.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
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.Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Hardcover. Etat : 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. N° de réf. du vendeur 9780471356295
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Hardcover. Etat : 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 Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. N° de réf. du vendeur 9780471356295
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