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Convergence of Dependent Random Variables: Central Limit Theorems, Berry-Esseen Bounds, Martingale-like Sequences, C-sequences, Strong Laws - Brossura
Sinossi
Central Limit Theorems, Rates of Convergence are derived for dependent random variables, with relaxed conditions on the dependence. Most of known mixing conditions like strong (alpha-) mixing, absolute regular (beta-mixing),... will satisfy them. This new notion of measure of dependence is developed naturally from the classical Characteristic Function Method, less intuitive but may be more suitable in applications than mixing ones. As it is born from the well-known tool for independent r.v.s's Limit Theorems. Theorems and examples given here prove this notion. Otherwise, it may reach the limit in process of defining measure of the dependence, as argued in this book. On the other aspect, almost sure convergence of adapted sequence, especially of Martingale-like one, is discussed. C-sequence is created, showed not comparative with Amart, Martingale-in-the-limit, by examples. It also is a natural extension of Martingale, derived by seeking condition ensuring a.s. convergence. Also, a phi-mixing Strong Law and some examples of Linear Process are given.
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L'autore
D. Q. Tuyen, Ph.D.: Graduated at Eötvös Loránd University in Budapest. Obtained Ph.D. at Karl-Weierstrass-Institute of Mathematics in Berlin. Researcher at Institute of Mathematics of Hanoi.
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Convergence of Dependent Random Variables
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LAP LAMBERT Academic Publishing Okt 2010, 2010
ISBN 10: 3843355622
ISBN 13: 9783843355629
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Central Limit Theorems, Rates of Convergence are derived for dependent random variables, with relaxed conditions on the dependence. Most of known mixing conditions like strong (alpha-) mixing, absolute regular (beta-mixing), will satisfy them. This new notion of measure of dependence is developed naturally from the classical Characteristic Function Method, less intuitive but may be more suitable in applications than mixing ones. As it is born from the well-known tool for independent r.v.s's Limit Theorems. Theorems and examples given here prove this notion. Otherwise, it may reach the limit in process of defining measure of the dependence, as argued in this book. On the other aspect, almost sure convergence of adapted sequence, especially of Martingale-like one, is discussed. C-sequence is created, showed not comparative with Amart, Martingale-in-the-limit, by examples. It also is a natural extension of Martingale, derived by seeking condition ensuring a.s. convergence. Also, a phi-mixing Strong Law and some examples of Linear Process are given. 124 pp. Englisch. Codice articolo 9783843355629
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Convergence of Dependent Random Variables
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ISBN 13: 9783843355629
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Convergence of Dependent Random Variables : Central Limit Theorems, Berry-Esseen Bounds, Martingale-like Sequences, C-sequences, Strong Laws
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LAP LAMBERT Academic Publishing, 2010
ISBN 10: 3843355622
ISBN 13: 9783843355629
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Central Limit Theorems, Rates of Convergence are derived for dependent random variables, with relaxed conditions on the dependence. Most of known mixing conditions like strong (alpha-) mixing, absolute regular (beta-mixing), will satisfy them. This new notion of measure of dependence is developed naturally from the classical Characteristic Function Method, less intuitive but may be more suitable in applications than mixing ones. As it is born from the well-known tool for independent r.v.s's Limit Theorems. Theorems and examples given here prove this notion. Otherwise, it may reach the limit in process of defining measure of the dependence, as argued in this book. On the other aspect, almost sure convergence of adapted sequence, especially of Martingale-like one, is discussed. C-sequence is created, showed not comparative with Amart, Martingale-in-the-limit, by examples. It also is a natural extension of Martingale, derived by seeking condition ensuring a.s. convergence. Also, a phi-mixing Strong Law and some examples of Linear Process are given. Codice articolo 9783843355629
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Convergence of Dependent Random Variables
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LAP LAMBERT Academic Publishing Okt 2010, 2010
ISBN 10: 3843355622
ISBN 13: 9783843355629
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Central Limit Theorems, Rates of Convergence are derived for dependent random variables, with relaxed conditions on the dependence. Most of known mixing conditions like strong (alpha-) mixing, absolute regular (beta-mixing), will satisfy them. This new notion of measure of dependence is developed naturally from the classical Characteristic Function Method, less intuitive but may be more suitable in applications than mixing ones. As it is born from the well-known tool for independent r.v.s''s Limit Theorems. Theorems and examples given here prove this notion. Otherwise, it may reach the limit in process of defining measure of the dependence, as argued in this book. On the other aspect, almost sure convergence of adapted sequence, especially of Martingale-like one, is discussed. C-sequence is created, showed not comparative with Amart, Martingale-in-the-limit, by examples. It also is a natural extension of Martingale, derived by seeking condition ensuring a.s. convergence. Also, a phi-mixing Strong Law and some examples of Linear Process are given.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 124 pp. Englisch. Codice articolo 9783843355629
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Convergence of Dependent Random Variables: Central Limit Theorems, Berry-Esseen Bounds, Martingale-like Sequences, C-sequences, Strong Laws
Editore:
LAP LAMBERT Academic Publishing, 2010
ISBN 10: 3843355622
ISBN 13: 9783843355629
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