关于可列非齐次马氏泛函的一类强偏差定理

A Class of Strong Deviation Theorems for Functionals of Countable Nonhomogeneous Markov Chains

引入样本相对熵率作为任意随机变量序列相对于可列非齐次马氏链的强偏差的一种度量来研究任意随机变量序列的极限性质,同时引入了一种全新的概率研究方法——分析法,得到了一类用不等式表示的强极限定理,即强偏差定理.

In this paper,the notion of sample relative entropy rate,as a measure of the difference between the sequence of random variables and Markov chains,is introduced,and by the use of this notion,a class of limit properties of the sequences of random variables considered on certain sets of the sample space are obtained,of which some strong laws for Markov Chains are special cases.