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141227t20141975vtu ob 001 0 eng d |
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|a 9781483191430
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|a 1483191435
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|a (OCoLC)898771933
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|2 23
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|a UAMI
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|a Ash, Robert B.
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|a Topics in stochastic processes /
|c Robert B. Ash, Melvin F. Gardner.
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|a Burlington :
|b Academic Press/Elsevier Science,
|c [2014], ©1975.
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|a 1 online resource (332 pages)
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
|2 rdacarrier
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|a Probability and mathematical statistics series: a series of monographs and textbooks ;
|v v. 27
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|a Includes bibliographical references and index.
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|a Print version record.
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|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.
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|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.
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|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.
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|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.
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520 |
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|a Topics in Stochastic Processes.
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590 |
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|a ProQuest Ebook Central
|b Ebook Central Academic Complete
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650 |
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|a Stochastic processes.
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650 |
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6 |
|a Processus stochastiques.
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650 |
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7 |
|a MATHEMATICS
|x Applied.
|2 bisacsh
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650 |
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7 |
|a MATHEMATICS
|x Probability & Statistics
|x General.
|2 bisacsh
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650 |
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|a Stochastic processes
|2 fast
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700 |
1 |
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|a Gardner, Melvin Frank,
|d 1944-
|1 https://id.oclc.org/worldcat/entity/E39PCjqCTRdVTfF9XQG9TVbgjy
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700 |
1 |
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|a Birnbaum, Z. W.
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700 |
1 |
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|a Lukacs, E.
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758 |
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|i has work:
|a Topics in stochastic processes (Text)
|1 https://id.oclc.org/worldcat/entity/E39PCGDqPTvPFXDbbBYwJdkPXq
|4 https://id.oclc.org/worldcat/ontology/hasWork
|
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.
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856 |
4 |
0 |
|u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=1901370
|z Texto completo
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938 |
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|a EBL - Ebook Library
|b EBLB
|n EBL1901370
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|a EBSCOhost
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