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| 权威性的专著。修订版增加了四章，并对原版内容作了大量修改。 |
| Preface to the Second Edition Preface to the First Edition 1. Measure Theory---Basic Notions 2. Measure Theory---Key Results 3. Processes, Distributions, and Independence 4. Random Sequences, Series, and Averages 5. Characteristic Functions and Classical Limit Theorems 6. Conditioning and Disintegration 7. Martingales and Optional Times 8. Markov Processes and Discrete-Time Chains 9. Random Walks and Renewal Theory 10. Stationary Processes and Ergodic Theory 11. Special Notions of Symmetry and Invariance 12. Poisson and Pure Jump-Type Markov Processes 13. Gaussian Processes and Brownian Motion 14. Skorohod Embedding and Invariance Principles 15. Independent Increments and Infinite Divisibility 16. Convergence of Random Processes, Measures, and Sets 17. Stochastic Integrals and Quadratic Variation 18. Continuous Martingales and Brownian Motion 19. Feller Processes and Semigroups 20. ergodic Properties of Markov Processes 21. Stochastic Differential Equations 22. Local Time, Excursions, and Additive Functionals 23. One-dimensional SDEs and Diffusions 24. Connections with PDEs and Potential Theory 25. Predictability, Compensation, and Excessive Functions 26. Semimartingales and General Stochastic Integration 27. Large Deviations Appendices Historical and Bibliographical Notes Bibliography Symbol Index Author Index Subject Index |
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