一类Markov链的强逼近

本文给出了一类非时齐的Markov链的强逼近.作为应用,建立了临床试验中Markov链自适应设计的强相合性,重对数律和弱收敛.     

Cayley树上随机场的马尔可夫逼近与一类小偏差定理

通过引进样本相对熵率作为Cayley树上任意随机场与马尔可夫链场之间的偏差的一种度量, 建立了关于状态序偶频率的一类小偏差定理. 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.     

关于任意随机变量序列泛函的强极限定理

本文在k是固定的正整数，{fn}是R^k 1上的Borel可测函数列时，得到了任意随机变量序列{Xrn≥0}的泛函{fn(Xn-k,…,Xn)}的强极限定理，它是Chung的关于独立随机变量序列的强大数律的推广，作为推论，得到了k重非齐次马尔科夫链的一类强极限定理．     

关于马氏环境中马氏链的强极限定理的注

利用鞅收敛定理讨论马氏环境中马氏链的强收敛性,建立相应的强大数定律,使得已知的一系列结果为其特例.     

A class of small deviation theorems for functionals of random fields on a homogeneous tree

By constructing a non-negative martingale on a homogeneous tree, a class of small deviation theorems for functionals of random fields, the strong law of large numbers for the frequencies of occurrence of states and ordered couple of states for random fields, and the asymptotic equipartition property (AEP) for finite random fields are established. As corollary, the strong law of large numbers and the AEP for Markov chains indexed by a Cayley tree is obtained. Some known results are generalized in this paper.     

Strong Markov Properties for Markov Random Fields

Markov properties and strong Markov properties for random fields are defined and discussed. Special attention is given to those defined by I. V. Evstigneev. The strong Markov nature of Markov random fields with respect to random domains such as [0, L], where L is a multidimensional extension of a stopping time, is explored. A special case of this extension is shown to generalize a result of Merzbach and Nualart for point processes. As an additional example, Evstigneev's Markov and strong Markov properties are considered for independent increment jump processes.     

双无限环境中马氏链的强大数定律

在随机环境中马氏链的研究领域 ,构造了一时齐的马氏双链 ,讨论了它的存在性及基本性质 ,最后利用马氏双链的性质 ,得到了双无限环境中马氏链的函数极限定律 ,并给出了该链的函数强大数定律成立的两个充分条件     

Strong laws of large numbers for asymptotic even–odd Markov chains indexed by a homogeneous tree

In this paper, we are going to study the strong laws of large numbers for asymptotic even–odd Markov chains indexed by a homogeneous tree. First, the definition of the asymptotic even–odd Markov chain is introduced. Then the strong limit theorem for asymptotic even–odd Markov chains indexed by a homogeneous tree is established. Next, the strong laws of large numbers for the frequencies of occurrence of states and ordered couple of states for asymptotic even–odd Markov chains indexed by a homogeneous tree are obtained. Finally, we prove the asymptotic equipartition property (AEP) for these Markov chains.     

Law of large numbers and central limit theorem for randomly forced PDE's

We consider a class of dissipative PDE's perturbed by an external random force. Under the condition that the distribution of perturbation is sufficiently non-degenerate, a strong law of large numbers (SLLN) and a central limit theorem (CLT) for solutions are established and the corresponding rates of convergence are estimated. It is also shown that the estimates obtained are close to being optimal. The proofs are based on the property of exponential mixing for the problem in question and some abstract SLLN and CLT for mixing-type Markov processes.     

CRITERIA OF STRONG TRANSIENCE FOR OPERATOR-SELF-SIMILAR MARKOV PROCESSES

Yamamuro in [1] defines strong and weak transience of Markov processes; gives a criterion for strong transience of Feller processes; and further, discusses strong and weak transience of Ornstein-Uhlenbeck type processes. In this article, the authors weaken the Feller property of the result in [1] to weak Feller property and discuss the strong transience of operator-self-similar Markov processes.     

A Class of Strong Deviation Theorems for the Random Fields Associated with Nonhomogeneous Markov Chains Indexed by a Bethe Tree

In this article, we establish a class of strong deviation theorems for the random fields which are associated with nonhomogeneous Markov chains indexed by a Bethe tree. As corollaries, we obtain the strong law of large numbers and asymptotic equipartition property for nonhomogeneous Markov chains indexed by such tree.     

Countably many simultaneous random changes of time scales

Simultaneous changes of time scales of the components of a vector Markov process are defined and developed. Measurability properties, Dynkin's lemma, and the strong Markov property are established for the transformed process.     

On Least Squares Estimation for Stable Nonlinear AR Processes

Following a Markov chain approach, this paper establishes asymptotic properties of the least squares estimator in nonlinear autoregressive (NAR) models. Based on conditions ensuring the stability of the model and allowing the use of a strong law of large number for a wide class of functions, our approach improves some known results on strong consistency and asymptotic normality of the estimator. The exact convergence rate is established by a law of the iterated logarithm. Based on this law and a generalized Akaike's information criterion, we build a strongly consistent procedure for selection of NAR models. Detailed results are given for familiar nonlinear AR models like exponential AR models, threshold models or multilayer feedforward perceptions.     

可列非齐次隐Markov模型的强大数定律

隐马尔科夫模型被广泛的应用于弱相依随机变量的建模,是研究神经生理学、发音过程和生物遗传等问题的有力工具。研究了可列非齐次隐 Markov 模型的若干性质,得到了这类模型的强大数定律,推广了有限非齐次马氏链的一类强大数定律。     

A Markov copula model with regime switching and its application

Regime switching, which is described by a Markov chain, is introduced in a Markov copula model. We prove that the marginals (X,H ⁱ ), i = 1, 2, 3 of the Markov copula model (X,H) are still Markov processes and have martingale property. In this proposed model, a pricing formula of credit default swap (CDS) with bilateral counterparty risk is derived.     

任意齐次树指标马氏链场的一类Shannon-Mcmillan定理

采用构造相容分布与非负上鞅的方法来研究任意齐次树指标可列非齐次马氏链场的相对熵密度的一类强极限定理,并由此得出若干齐次树指标有限状态非齐次马氏链场、一般非齐次马氏链的Shannon-Mcmillan定理.将已有的关于离散信源的结果加以推广.     

Branching Markov processes and related asymptotics

Models for Markov processes indexed by a branching process are presented. The new class of models is referred to as the branching Markov process (BMP). The law of large numbers and a central limit theorem for the BMP are established. Bifurcating autoregressive processes (BAR) are special cases of the general BMP model discussed in the paper. Applications to parameter estimation are also presented.     

关于m阶非齐次马氏信源的一类Shannon-McMillan定理

采用构造相容分布与非负上鞅的方法的研究m阶马氏信源广义相对熵密度的强极限定理,即广义Shannon-McMillan定理.并由此得出若干马氏信源,无记忆信源的随机Shannon-Mcmillan定理.将已有的马氏信源的结果加以推广     

Hyperbolic structure preserving isomorphisms of Markov shifts. II

This paper is a continuation of [14] and deals with metric isomorphisms of Markov shifts which are finitary and hyperbolic structure preserving. We prove that theβ-function introduced by S. Tuncel in [15] is an invariant of such isomorphisms. Following [5] this result is extended to Gibbs measures arising from functions with summable variation. Finally we prove that, for anyC ² Axiom A diffeomorphism on a basic set Ω, and for any equilibrium state associated with a Hölder continuous function on Ω, the Markov shifts arising from different Markov partitions of Ω are isomorphic via a finitary, hyperbolic structure preserving isomorphism. This fact leads to a rich class of examples of such isomorphisms (other examples are provided by finitary isomorphisms of Markov shifts with finite expected code lengths — cf. [14]).