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Viser: Foundations of Modern Probability
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Foundations of Modern Probability Vital Source e-bog
Olav Kallenberg
(2019)
Springer Nature
897,00 kr.
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Foundations of Modern Probability
Olav Kallenberg
(2002)
Sprog: Engelsk
Springer New York
1.142,00 kr.
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Detaljer om varen
- 2. Udgave
- Vital Source searchable e-book (Fixed pages)
- Udgiver: Springer Nature (Juni 2019)
- ISBN: 9781475740158
From the reviews of the first edition: "...Kallenberg's present book would have to qualify as the assimilation of probability par excellence. It is a great edifice of material, clearly and ingeniously presented, without any non-mathematical distractions. Readers wishing to venture into it may do so with confidence that they are in very capable hands." F.B. Knight, Mathematical Reviews This new edition contains four new chapters as well as numerous improvements throughout the text.
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Print: 2 sider kan printes ad gangen
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Bookshelf online: 5 år fra købsdato.
Bookshelf appen: ubegrænset dage fra købsdato.
Udgiveren oplyser at følgende begrænsninger er gældende for dette produkt:
Print: 2 sider kan printes ad gangen
Copy: højest 2 sider i alt kan kopieres (copy/paste)
Detaljer om varen
- Hardback: 664 sider
- Udgiver: Springer New York (Januar 2002)
- ISBN: 9780387953137
The first edition of this single volume on the theory of probability has become a highly-praised standard reference for many areas of probability theory. Chapters from the first edition have been revised and corrected, and this edition contains four new chapters. New material covered includes multivariate and ratio ergodic theorems, shift coupling, Palm distributions, Harris recurrence, invariant measures, and strong and weak ergodicity.
* Measure Theory-Basic Notions * Measure Theory-Key Results * Processes, Distributions, and Independence * Random Sequences, Series, and Averages * Characteristic Functions and Classical Limit Theorems * Conditioning and Disintegration * Martingales and Optional Times * Markov Processes and Discrete-Time Chains * Random Walks and Renewal Theory * Stationary Processes and Ergodic Theory * Special Notions of Symmetry and Invariance * Poisson and Pure Jump-Type Markov Processes * Gaussian Processes and Brownian Motion * Skorohod Embedding and Invariance Principles * Independent Increments and Infinite Divisibility * Convergence of Random Processes, Measures, and Sets * Stochastic Integrals and Quadratic Variation * Continuous Martingales and Brownian Motion * Feller Processes and Semigroups * Ergodic Properties of Markov Processes * Stochastic Differential Equations and Martingale Problems * Local Time, Excursions, and Additive Functionals * One-Dimensional SDEs and Diffusions * Connections with PDEs and Potential Theory * Predictability, Compensation, and Excessive Functions * Semimartingales and General Stochastic Integration * Large Deviations *
Appendix 1: Advanced Measure Theory *
Appendix 2: Some Special Spaces * Historical and Bibliographical Notes * Bibliography * Indices
Appendix 1: Advanced Measure Theory *
Appendix 2: Some Special Spaces * Historical and Bibliographical Notes * Bibliography * Indices
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