Some strong limit theorems for nonhomogenous markov chains in random environments;
利用分析方法研究了马氏环境中马氏链的若干强极限定理。
The strong limit theorems for Markov chain fields indexed on the arbitrary Bethe tree are studied.
利用分析方法研究了马氏环境中马氏链的若干强极限定理。
In the proof a new analytic technique in the study of the strong limit theorems for Markov chains is applied.
证明中应用了研究马尔可夫链强极限定理的一种新的分析方法。
The purpose of this paper is to present a class of new strong limit theorems on the frequency ofm-tuple of states for arbitrary countable non-homogeneous Markov chains.
本文的目的是要给出关于可列非齐次马尔可夫链M元状态序组出现频率的一类新形式的强极限定理，所得结论对任意可列非齐次马尔可夫链普遍成立。
The strong limit theorems on the arbitrary stochastic convergence for the harmonic mean of the random conditional probabilities in the random selection system is studied.
主要研究任意随机序列在随机选择系统中的随机条件概率其调和平均的强极限定理。
In the proof, the tools of the conditional moment generating function and the differentiation on a net for the study on strong limit theorems in the random selection system are applied.
在证明中采用了一种把网微分法与条件矩母函数相结合应用于随机选择系统强极限定理研究的一种途径。
As corollaries, we obtain some strong limit theorems for the frequencies of occurrence of states and ordered couples of states for the even-odd Markov chain fields and Markov chain fields.
作为这一类强极限定理的推论得到了状态和状态序偶出现频率的一类强极限定理。
Probability limit theorems surveyed mainly involved strong laws of large Numbers, rates of convergence, convergence in distribution and large deviation principles.
涉及的概率极限定理包括强大数律，收敛速度，依分布收敛和大偏差原理。
Probability limit theorems surveyed mainly involved strong laws of large Numbers, rates of convergence, convergence in distribution and large deviation principles.
涉及的概率极限定理包括强大数律，收敛速度，依分布收敛和大偏差原理。
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