一类随机适应序列部分和的局部极限定理的一个注记

研究了一类随机适应序列的强极限定理,推广了最近发表的几个结果,并进一步推广了Borel—Cantelli引理．     

A local convergence theorem for partial sums of stochastic adapted sequences

In this paper we establish a new local convergence theorem for partial sums of arbitrary stochastic adapted sequences. As corollaries, we generalize some recently obtained results and prove a limit theorem for the entropy density of an arbitrary information source, which is an extension of case of nonhomogeneous Markov chains.     

非齐次树上马氏双链的一个强极限定理

树指标随机过程已成为近年发展起来的概率论的研究方向之一.强极限定理一直是国际概率论界研究的中心课题之一.通过构造适当的非负鞅,将Doob鞅收敛定理应用于几乎处处收敛的研究,研究给出了一类非齐次树上马氏双链的一个强极限定理.     

非齐次树上马氏链的若干强偏差定理

通过构造适当的非负鞅,将Doob鞅收敛定理应用于几乎处处收敛的研究,给出了一类非齐次树上马氏链场加权和滑动平均的若干强偏差定理.     

关于任意随机适应序列部分和的一类局部极限定理

研究任意随机适应序列部分和的一类局部极限定理,推广了最近发表的几个结果．     

On the strong law of large numbers for functionals of countable nonhomogeneous Markov chains

We prove a strong law of large numbers for functionals of nonhomogeneous Markov chains. The approach is analytic and different from the usual one.     

A class of strong limit theorems for inhomogeneous Markov chains indexed by a generalized Bethe tree on a generalized random selection system

We study strong limit theorems for a sequence of bivariate functions for an inhomogeneous Markov chain indexed by a generalized Bethe tree on a generalized random selection system by constructing a nonnegative martingale. As corollaries, we generalize results of Yang and Ye and obtain some limit theorems for frequencies of states, ordered couples of states, and the conditional expectation of a bivariate function on a Cayley tree.     

Strong law of large numbers for countable nonhomogeneous Markov chains

The aim of this paper is to establish a strong law of large numbers for the bivariate functions of countable nonhomogeneous Markov chains under the condition of uniform convergence in the Cesàro sense which differs from my previous results. As corollaries, we generalize one of the Liu and Liu’s results for the univariate functions case and obtain another Shannon–McMillan–Breiman theorem for this Markov chains.     

关于非齐次马氏链的一个定理

给出了Csiszar和Krner关于独立随机变量序列的一个定理的一个推广,该定理的推论是关于相对熵的,在统计假设检验及编码理论中起着重要的作用.利用非齐次马氏链的一个强大数定律将这个定理推广到非齐次马氏链上.     

A strong limit theorem on gambling systems

A strong limit theorem on gambling system for Bernoulli sequences is extended to the sequences of arbitrary discrete random variables by using the conditional probabilities. Furthermore, by allowing the selection function to take values in an interval, the conception of random selection is generalized. In the proof an approach of applying the differentiation of measure on a net to the investigation of the strong limit theorem is proposed.     

A ratio limit theorem for the finite nonhomogeneous Markov chains

A new simple proof concerning the structure of the tail σ-field of a nonhomogeneous Markov chain as well as a result regarding the asymptotic behaviour of the ratio between the transition probabilities and the absolute probabilities of the chain are given. It is shown that the latter result can be used to characterize the atomic sets of the tail σ-field.     

Central limit theorems for a class of irreducible multicolor urn models

We take a unified approach to central limit theorems for a class of irreducible multicolor urn models with constant replacement matrix. Depending on the eigenvalue, we consider appropriate linear combinations of the number of balls of different colors. Then under appropriate norming the multivariate distribution of the weak limits of these linear combinations is obtained and independence and dependence issues are investigated. Our approach consists of looking at the problem from the viewpoint of recursive equations.     

非齐次树上马氏信源的一类Shannon-McMillan定理

通过构造适当的非负鞅,将Doob鞅收敛定理应用于几乎处处收敛的研究,给出了非齐次树上m重非齐次马氏信源的一类Shannon-McMillan定理.     

A strong limit theorem for generalized Cantor-like random sequences

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任意信源关于赌博系统的一类Shannon-McMillan定理

采用网微分法和分析运算方法来研究赌博系统中任意随机变量序列随机条件熵的一类强极限定理,并由此得出若干任意信源的Shannon-Mcmillan定理.将已有的关于离散信源的结果加以推广.     

非齐次隐马尔可夫模型随机变换的若干强极限定理

利用鞅方法讨论了非齐次隐马尔可夫模型变换的强极限定理,作为特殊情形,将随机选择的概念拓展到非齐次隐马尔可夫模型中,得到了关于有限非齐次隐马尔可夫模型随机选择与随机公平比的若干极限定理.     

A central limit theorem for the sojourn times of strongly ergodic Markov chains

Let X_n be an irreducible aperiodic recurrent Markov chain with countable state space I and with the mean recurrence times having second moments. There is proved a global central limit theorem for the properly normalized sojourn times. More precisely, if $\text{t}{}^{\mathrm{(n}}\text{)}{}_{\mathrm{i}}\text{=Σ}{}^{\mathrm{n}}{}_{\mathrm{k=1}}\text{i}\text{?}{}_{\mathrm{i}}\text{(X}{}_{\mathrm{k}}\text{)}$, then the probability measures induced by {t⁽ⁿ⁾_i/√n?√nπ_i}_i?I(π_i being the ergotic distribution) on the Hilbert-space of square summable I-sequences converge weakly in this space to a Gaussian measure determined by a certain weak potential operator.     

关于微分熵的一类强偏差定理

利用关于乘积分布密度的相对熵和相对熵率的概念,建立了相依连续型随机变量序列关于参考微分熵的一类强偏差定理,证明中给出了将Laplace变换应用于微分熵强偏差定理的研究的一种途径．     

Classical limit theorems for measure-valued Markov processes

Laws of large numbers, central limit theorems, and laws of the iterated logarithm are obtained for discrete and continuous time Markov processes whose state space is a set of measures. These results apply to each measure-valued stochastic process itself and not simply to its real-valued functionals.     

Central limit theorems for ergodic continuous-time Markov chains with applications to single birth processes

We obtain sufficient criteria for central limit theorems (CLTs) for ergodic continuous-time Markov chains (CTMCs). We apply the results to establish CLTs for continuous-time single birth processes. Moreover, we present an explicit expression of the time average variance constant for a single birth process whenever a CLT exists. Several examples are given to illustrate these results.