现代概率论基础 英文版PDF电子书下载

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1．Elements of Measure Theory 1

2．Processes，Distributions，and Independence 22

3．Random Sequences，Series，and Averages 39

4．Characteristic Functions and Classical Limit Theorems 60

5．Conditioning and Disintegration 80

6．Martingales and Optional Times 96

7．Markov Processes and Discrete-Time Chains 117

8．Random Walks and Renewal Theory 136

9．Stationary Processes and Ergodic Theory 156

10．Poisson and Pure Jump-Type Markov Processes 176

11．Gaussian Processes and Brownian Motion 199

12．Skorohod Embedding and Invariance Principles 220

13．Independent Increments and Infinite Divisibility 234

14．Convergence of Random Processes，Measures，and Sets 255

15．Stochastic Integrals and Quadratic Variation 275

16．Continuous Martingales and Brownian Motion 296

17．Feller Processes and Semigroups 313

18．Stochastic Differential Equations and Martingale Problems 335

19．Local Time，Excursions，and Additive Functionals 350

20．One-Dimensional SDEs and Diffusions 371

21．PDE-Connections and Potential Theory 390

22．Predictability,Compensation，and Excessive Functions 409

23．Semimartingales and General Stochastic Integration 433

Appendices 455

Historical and Bibliographical Notes 464

Bibliography 486

Indices 509

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