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* 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
• Shastic Integrals and Quadratic Variation
• Continuous Martingales and Brownian Motion
• Feller Processes and Semigroups
• Ergodic Properties of Markov Processes
• Shastic 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 Shastic Integration
• Large Deviations
• Appendix 1: Advanced Measure Theory
• Appendix 2: Some Special Spaces
• Historical and Bibliographical Notes
• Bibliography
• Indices
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Add Foundations of Modern Probability, From the reviews of the first editions: ... 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, Foundations of Modern Probability to the inventory that you are selling on WonderClubX
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Add Foundations of Modern Probability, From the reviews of the first editions: ... 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, Foundations of Modern Probability to your collection on WonderClub |