概率与测度论:(英文影印版.第2版)(赠品)

. 3.2 basic properties of hilbert spaces
3.3 linear operators on normed linear spaces
3.4 basic theorems of functional analysis
3.5 references
4 basic concepts of probability
　4.1 introduction
　4.2 discrete probability spaces
　4.3 independence
　4.4 bernoulli trials
　4.5 conditional probability
　4.6 random variables
　4.7 random vectors
　4.8 independent random variables
　4.9 some examples from basic probability
　4.10 expectation
　4.11 infinite sequences of random variables
　4.12 references
5 conditional probability and expectation
　5.1 introduction
　5.2 applications
　5.3 the general concept of conditional probability and expectation
　5.4 conditional expectation given a o-field
　5.5 properties of conditional expectation
　5.6 regular conditional probabilities
6 strong laws of large numbers and martingale theory
　6.1 introduction
　6.2 convergence theorems
　6.3 martingales
　6.4 martingale convergence theorems
　6.5 uniform integrability
　6.6 uniform integrability and martingale theory
　6.7 optional sampling theorems
　6.8 applications of martingale theory
　6.9 applications to markov chains
　6.10 references
7 the central limit theorem
　7.1 introduction
　7.2 the fundamental weak compactness theorem
　7.3 convergence to a normal distribution
……
8 ergodic theory
9 brownian motion and stochastic integrals
appendices
bibliography
solutions to problems
index