Topics in Infinitely Divisible Distributions and L?vy Processes, Revised Edition, Alfonso Rocha-Arteaga; Ken-iti Sato

Автор: Olivier Thas
Название: Comparing Distributions
ISBN: 1461424496 ISBN-13(EAN): 9781461424499
Издательство: Springer
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Цена: 153720.00 T
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Описание: This volume provides a theoretical treatment of a wide range of goodness-of-fit statistical methods. By comparing techniques for both one-sample and k-sample problems, the text offers a wider perspective that considers graphic and estimation parameters, and emphasizes their theoretical similarities.

Автор: Wright Calanthia
Название: Statistical Distributions
ISBN: 1682851648 ISBN-13(EAN): 9781682851647
Издательство: Неизвестно
Цена: 160930.00 T
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Описание: Statistical distribution aims to measure different subsets of a possible outcome by assigning a probability and is beneficial in random surveys. It is further divided into various sub-categories and has wide ranging applications in diverse scientific and engineering fields. The book focuses upon discrete, continuous and mixed probability distributions with detailed examples. It provides various graphs and methodologies to measure the sample space of random variables. Applied probability is extensively discussed in this book through different researches which makes it a very helpful reference source for students, researchers and academicians.

Автор: Sato
Название: L?vy Processes and Infinitely Divisible Distributions
ISBN: 1107656494 ISBN-13(EAN): 9781107656499
Издательство: Cambridge Academ
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Описание: This successful text provides a comprehensive basic knowledge of Levy processes and serves as an introduction to stochastic processes in general. Now in paperback, this corrected edition contains a brand new supplement discussing relevant developments in the area since the book`s initial publication.

Автор: Benjamin Arras; Christian Houdr?
Название: On Stein`s Method for Infinitely Divisible Laws with Finite First Moment
ISBN: 303015016X ISBN-13(EAN): 9783030150167
Издательство: Springer
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Цена: 46570.00 T
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Описание: This book focuses on quantitative approximation results for weak limit theorems when the target limiting law is infinitely divisible with finite first moment. Two methods are presented and developed to obtain such quantitative results. At the root of these methods stands a Stein characterizing identity discussed in the third chapter and obtained thanks to a covariance representation of infinitely divisible distributions. The first method is based on characteristic functions and Stein type identities when the involved sequence of random variables is itself infinitely divisible with finite first moment. In particular, based on this technique, quantitative versions of compound Poisson approximation of infinitely divisible distributions are presented. The second method is a general Stein's method approach for univariate selfdecomposable laws with finite first moment. Chapter 6 is concerned with applications and provides general upper bounds to quantify the rate of convergence in classical weak limit theorems for sums of independent random variables. This book is aimed at graduate students and researchers working in probability theory and mathematical statistics.

Автор: Arnold Janssen; Hartmut Milbrodt; Helmut Strasser
Название: Infinitely Divisible Statistical Experiments
ISBN: 0387960554 ISBN-13(EAN): 9780387960555
Издательство: Springer
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Цена: 97820.00 T
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Описание: This book is intended to give an account of the theory of infi- nitely divisible statistical experiments which started from LeCam, 1974. It includes a presentation of LeCam's basic results as well as new developments in the field. The book consists of four chapters written by different authors. Chapters I, III and IV have been prepared in Bayreuth with the support of the Deutsche Forschungsgemeinschaft (DFG); Chapter II is part of its author's Habilitationsschrift, 1982 (Dortmund). For the reader's convenience, the chapters have been unified in presentation, without neglecting differences in the individual styles of writing. The authors are grateful to Dr. C. Becker for carefully reviewing the manuscript. Furthermore, acknowledgements are gratefully extended to the DFG for partly subsidizing Dr. Becker and the second author by a grant. Some special words of thanks are due to Mrs. Witzigmann, who typed the final manuscript and its predecessors with patience and skill. Universitat Bayreuth und A. Janssen Universitat Dortmund, H. Milbrodt Dezember 1984 H. Strasser CONTENTS Preface Introduction L its of Triangular Arrays of 14 I. EXEeriments (H. Milbrodt and H. Strasser) 1. Basic Concepts 14 19 2. Gaussian Exper ents 3. Introduction to Poisson Experiments 25 4. Convergence of Poisson Experiments 32 5. Convergence of Triangular Arrays 38 6. Identification of Limit Experiments 47 The Levy-Khintchine Formula for Infinitely 55 II.

Автор: A. Liemant; K. Matthes; A. Wakolbinger
Название: Equilibrium Distributions of Branching Processes
ISBN: 9027727740 ISBN-13(EAN): 9789027727749
Издательство: Springer
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Автор: Barry C. Arnold; Enrique Castillo; Jose-Maria Sara
Название: Conditionally Specified Distributions
ISBN: 0387977945 ISBN-13(EAN): 9780387977942
Издательство: Springer
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Цена: 111790.00 T
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Описание: The concept of conditional specification is not new. Arnold Riverside, California USA Enrique Castillo Jose Maria Sarabia Santander, Cantabria Spain January, 1991 Contents 1 Conditional Specification 1 1.1 Why? . 2 1.3 Early work on conditional specification 4 1.4 Organization of this monograph . . . . . . . . . . . . . . . . . . . . . . . . . . .

Автор: Gordon E. Willmot; X. Sheldon Lin
Название: Lundberg Approximations for Compound Distributions with Insurance Applications
ISBN: 0387951350 ISBN-13(EAN): 9780387951355
Издательство: Springer
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Цена: 83850.00 T
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Описание: These notes represent our summary of much of the recent research that has been done in recent years on approximations and bounds that have been developed for compound distributions and related quantities which are of interest in insurance and other areas of application in applied probability.

Автор: N. Balakrishnan; W.S. Chen
Название: Handbook of Tables for Order Statistics from Lognormal Distributions with Applications
ISBN: 0792356349 ISBN-13(EAN): 9780792356349
Издательство: Springer
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Цена: 259950.00 T
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Описание: Presents elaborate tables of moments of order statistics as well as BLUES based on complete and censored samples for lognormal distributions. This title includes various illustrative examples for the different uses of these tables pertaining to inference and prediction.

Автор: Duangkamon Chotikapanich
Название: Modeling Income Distributions and Lorenz Curves
ISBN: 1441924930 ISBN-13(EAN): 9781441924933
Издательство: Springer
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Цена: 194730.00 T
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Описание: The parameterization of income distributions using Lorenz Curves is a useful technique to analyze the characteristics of income inequality within a given population. This book brings together classic papers in the field including cutting-edge contributions.

Автор: Sergey Foss; Dmitry Korshunov; Stan Zachary
Название: An Introduction to Heavy-Tailed and Subexponential Distributions
ISBN: 1461471001 ISBN-13(EAN): 9781461471004
Издательство: Springer
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Цена: 46570.00 T
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Описание: Heavy-tailed probability distributions are an important component in the modeling of many stochastic systems.

Автор: G.G. Hamedani
Название: Characterizations of Recently Introduced Univariate Continuous Distributions II
ISBN: 1536150959 ISBN-13(EAN): 9781536150957
Издательство: Nova Science
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Описание: This monograph is, as far as the author has gathered, the second of its kind (the first one was published by Nova in 2017 with coauthors Hamedani and Maadooliat) which presents various characterizations of a wide variety of continuous distributions. These two monographs could also be used as sources to prevent reinventing and duplicating the already exiting distributions. The current book consists of seven chapters. The first chapter lists cumulative and density functions of two hundred and twenty univariate distributions. Chapter two provides characterizations of these distributions: (i) based on the ration of two truncated moments; (ii) in terms of the hazard function; (iii) in terms of the reverse hazard function; (iv) based on the conditional expectation of certain functions of the random variable. Chapter three includes the characterizations of twenty distributions, which appeared in a published paper (Hamedani and Safavimanesh, 2017). Chapter four presents characterizations of thirty six distributions, contains a published paper (Hamedani, 2017). Chapter five covers the characterizations of forty one distributions, which appeared in a published paper (Hamedani, 2018a). Chapter six presents characterizations of eighty distributions, contained in a published paper (Hamedani, 2018b). Finally, chapter seven consists of seventy proposed distributions. The main reason to include previously published papers in Chapters 3-6 is to provide a rather complete source for the interested researchers who would want to avoid reinventing the existing distributions.