Probability : theory and examples
著者
書誌事項
Probability : theory and examples
（Cambridge series on statistical and probabilistic mathematics）
Cambridge University Press, 2010
4th ed
- : hbk
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注記
Includes bibliographical references (p. 419-424) and index
内容説明・目次
内容説明
This classic introduction to probability theory for beginning graduate students covers laws of large numbers, central limit theorems, random walks, martingales, Markov chains, ergodic theorems, and Brownian motion. It is a comprehensive treatment concentrating on the results that are the most useful for applications. Its philosophy is that the best way to learn probability is to see it in action, so there are 200 examples and 450 problems. The fourth edition begins with a short chapter on measure theory to orient readers new to the subject.
目次
- 1. Measure theory
- 2. Laws of large numbers
- 3. Central limit theorems
- 4. Random walks
- 5. Martingales
- 6. Markov chains
- 7. Ergodic theorems
- 8. Brownian motion
- Appendix A. Measure theory details.
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