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Topics in stochastic processes /

Topics in Stochastic Processes.

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Ash, Robert B.
Otros Autores: Gardner, Melvin Frank, 1944-, Birnbaum, Z. W., Lukacs, E.
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Burlington : Academic Press/Elsevier Science, [2014], ©1975.
Colección:Probability and mathematical statistics ; v. 27.
Temas:
Acceso en línea:Texto completo

MARC

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245 1 0 |a Topics in stochastic processes /  |c Robert B. Ash, Melvin F. Gardner. 
260 |a Burlington :  |b Academic Press/Elsevier Science,  |c [2014], ©1975. 
300 |a 1 online resource (332 pages) 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
490 1 |a Probability and mathematical statistics series: a series of monographs and textbooks ;  |v v. 27 
504 |a Includes bibliographical references and index. 
588 0 |a Print version record. 
505 0 |a Front Cover; Topics in Stochastic Processes; Copyright Page; Table of Contents; PREFACE; Chapter 1. L2 Stochastic Processes; 1.1 Introduction; 1.2 Covariance Functions; 1.3 Second Order Calculus; 1.4 Karhunen-Loève Expansion; 1.5 Estimation Problems; 1.6 Notes; Chapter 2. Spectral Theory and Prediction; 2.1 Introduction; L2 Stochastic Integrals; 2.2 Decomposition of Stationary Processes; 2.3 Examples of Discrete Parameter Processes; 2.4 Discrete Parameter Prediction: Special Cases; 2.5 Discrete Parameter Prediction: General Solution; 2.6 Examples of Continuous Parameter Processes. 
505 8 |a 2.7 Continuous Parameter Prediction in Special Cases Yaglom's Method; 2.8 Some Stochastic Differential Equations; 2.9 Continuous Parameter Prediction: Remarks on the General Solution; 2.10 Notes; Chapter 3. Ergodic Theory; 3.1 Introduction; 3.2 Ergodicity and Mixing; 3.3 The Pointwise Ergodic Theorem; 3.4 Applications to Real Analysis; 3.5 Applications to Markov Chains; 3.6 The Shannon-McMillan Theorem; 3.7 Notes; Chapter 4. Sample Function Analysis of Continuous Parameter Stochastic Processes; 4.1 Separability; 4.2 Measurability; 4.3 One-Dimensional Brownian Motion. 
505 8 |a 4.4 Law of the Iterated Logarithm4.5 Markov Processes; 4.6 Processes with Independent Increments; 4.7 Continuous Parameter Martingales; 4.8 The Strong Markov Property; 4.9 Notes; Chapter 5. The Itô Integral and Stochastic Differential Equations; 5.1 Definition of the Itô Integral; 5.2 Existence and Uniqueness Theorems for Stochastic Differential Equations; 5.3 Stochastic Differentials: A Chain Rule; 5.4 Notes; Appendix 1: Some Results from Complex Analysis; A1.1 Definitions and Comments; A1.2 Lemma; A1.3 Fatou's Radial Limit Theorem; A1.4 The Space H; A1.5 Theorem; A1.6 Theorem; A1.7 Theorem. 
505 8 |a Appendix 2: Fourier Transforms on the Real LineA2.1 Some Basic Properties; A2.2 Lemma; A2.3 Lemma; A2.4 Lemma; A2.5 Inversion Theorem; A2.6 Fourier-Plancherel Theorem; References; Solutions to Problems; Index. 
520 |a Topics in Stochastic Processes. 
590 |a ProQuest Ebook Central  |b Ebook Central Academic Complete 
650 0 |a Stochastic processes. 
650 6 |a Processus stochastiques. 
650 7 |a MATHEMATICS  |x Applied.  |2 bisacsh 
650 7 |a MATHEMATICS  |x Probability & Statistics  |x General.  |2 bisacsh 
650 7 |a Stochastic processes  |2 fast 
700 1 |a Gardner, Melvin Frank,  |d 1944-  |1 https://id.oclc.org/worldcat/entity/E39PCjqCTRdVTfF9XQG9TVbgjy 
700 1 |a Birnbaum, Z. W. 
700 1 |a Lukacs, E. 
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776 0 8 |i Print version:  |a Ash, Robert B.  |t Topics in Stochastic Processes : Probability and Mathematical Statistics: A Series of Monographs and Textbooks.  |d Burlington : Elsevier Science, ©2014  |z 9780120652709 
830 0 |a Probability and mathematical statistics ;  |v v. 27. 
856 4 0 |u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=1901370  |z Texto completo 
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