随机变量和分布函数,测度论,数学期望,方差,各种收敛性,大数律, **极限定理,特征函数,随机游动, 马氏性和鞅理论.本书内容丰富,逻辑紧密,叙述严谨,不仅可以扩展读者的视野,而且还将为其后续的学习和研究打下坚实基础。此外,本书的习题较多, 都经过细心的遴选, 从易到难, 便于读者巩固练习。本版补充了有关测度和积分方面的内容,并增加了一些习题。
本书是一本享誉世界的经典概率论教材,令众多读者受益无穷,自出版以来,已被世界75%以上的大学的数万名学生使用。本书内容丰富,逻辑清晰,叙述严谨,不仅可以拓展读者的视野,而且还将为其后续的学习和研究打下坚实���础。此外,本书的习题较多, 都经过细心的遴选, 从易到难, 便于读者巩固练习。本版补充了有关测度和积分方面的内容,并增加了一些习题。

Preface to the third edition
Preface to the second edition
Preface to the first edition
1 Distribution function
1.1 Monotone functions
1.2 Distribution functions
1.3 Absolutely continuous and singular distributions
2 Measure theory
2.1 Classes of sets
2.2 Probability measures and their distribution functions
3 Random variable. Expectation. Independence
3.1 General definitions
3.2 Properties of mathematical expectation
3.3 Independence
4 Convergence concepts
4.1 Various modes of convergence
4.2 Almost sure convergence; Borel-Cantelli lemma
4.3 Vague convergence
4.4 Continuation
4.5 Uniform integrability; convergence of moments
5 Law of large numbers. Random series
5.1 Simple limit theorems
5.2 Weak law of large numbers
5.3 Convergence of series
5.4 Strong law of large numbers
5.5 Applications
Bibliographical Note
6 Characteristic function
6.1 General properties; convolutions
6.2 Uniqueness and inversion
6.3 Convergence theorems
6.4 Simple applications
6.5 Representation theorems
6.6 Multidimensional case; Laplace transforms
Bibliographical Note
7 Central limit theorem and its ramifications
7.1 Liapounov's theorem
7.2 Lindeberg-Feller theorem
7.3 Ramifications of the central limit theorem
7.4 Error estimation
7.5 Law of the iterated logarithm
7.6 Infinite divisibility
Bibliographical Note
8 Random walk
8.1 Zero-or-one laws
8.2 Basic notions
8.3 Recurrence
8.4 Fine structure
8.5 Continuation
Bibliographical Note
9 Conditioning. Markov property. Martingale
Bibliographical Note
Supplement: Measure and Integral
General Bibliography
Index