Relaxation of Product Markov Chains on Product Spaces

We study the relaxation time of product-type Markov chains approaching a product distribution. We bound the approach to stationarity for such Markov chains in terms of the mixing times of the component Markov chains. In cases where the component mixing times differ considerably we propose an optimized visiting scheme which makes such product-type Markov chains comparable to Gibbs-type samplers. We conclude the paper by discussing the relaxation of Metropolis-type samplers for separable energy functions.     

Imprecise Markov chains with absorption

We consider convergence of Markov chains with uncertain parameters, known as imprecise Markov chains, which contain an absorbing state. We prove that under conditioning on non-absorption the imprecise conditional probabilities converge independently of the initial imprecise probability distribution if some regularity conditions are assumed. This is a generalisation of a known result from the classical theory of Markov chains by Darroch and Seneta [6].     

Estimations pour les chaînes de Markov réversibles

We give Gaussian lower and upper bounds for reversible Markov chains on a graph under two geometric assumptions (volume regularity and Poincaré inequality). This is first proved for continuous-time Markov chains via a parabolic Harnack inequality. Then, the estimates for the discrete-time Markov chains are derived by comparison.     

树指标马氏链的若干性质

主要研究了树指标马氏链的若干性质,它与一般直线上的马氏链有类似的性质.     

Regularity of Harmonic Functions for Some Markov Chains with Unbounded Range

We consider a class of continuous time Markov chains on ? ^d . These chains are the discrete space analogue of Markov processes with jumps. Under some conditions, as we show, harmonic functions associated with these Markov chains are Hölder continuous.     

Markov Chains Competing for Transitions: Application to Large-Scale Distributed Systems

We consider the behavior of a stochastic system composed of several identically distributed, but non independent, discrete-time absorbing Markov chains competing at each instant for a transition. The competition consists in determining at each instant, using a given probability distribution, the only Markov chain allowed to make a transition. We analyze the first time at which one of the Markov chains reaches its absorbing state. We obtain its distribution and its expectation and we propose an algorithm to compute these quantities. We also exhibit the asymptotic behavior of the system when the number of Markov chains goes to infinity. Actually, this problem comes from the analysis of large-scale distributed systems and we show how our results apply to this domain.     

Remarks on the speed of convergence of mixing coefficients and applications

We study dependence coefficients for copula-based Markov chains. We provide new tools to check the convergence rates of mixing coefficients of copula-based Markov chains. We apply results to the Metropolis–Hastings algorithm. A necessary condition for symmetric copulas is given and mixtures of copulas are studied.     

Convergence of locally and globally interacting Markov chains

We study the long run behaviour of interactive Markov chains on infinite product spaces. In view of microstructure models of financial markets, the interaction has both a local and a global component. The convergence of such Markov chains is analyzed on the microscopic level and on the macroscopic level of empirical fields. We give sufficient conditions for convergence on the macroscopic level. Using a perturbation of the Dobrushin–Vasserstein contraction technique we show that macroscopic convergence implies weak convergence of the underlying Markov chain. This extends the basic convergence theorem of Vasserstein for locally interacting Markov chains to the case where an additional global component appears in the interaction.     

一类特殊非齐次树上马氏链的若干强大数定律

首先给出了一类特殊非齐次树上可数状态马氏链的局部收敛定理,作为推论,得到了此类树上可数状态马氏链关于状态与状态序偶出现频率的若干极限性质,最后得到了这类特殊非齐次树上有限状态马氏链关于状态与状态序偶出现频率的强大数定律.     

On the mixing property and the ergodic principle for nonhomogeneous Markov chains

We study different types of limit behavior of infinite dimension discrete time nonhomogeneous Markov chains. We show that the geometric structure of the set of those Markov chains which have asymptotically stationary density depends on the considered topologies. We generalize and correct some results from Ganikhodjaev et al. (2006) [3].     

用耦合方法研究马氏链f-指数遍历

该文在一般状态空间下研究马氏链指数遍历性,指数遍历马氏链,增加条件π(f~p)<∞, p> 1,利用耦合方法得到了存在满的吸收集,使得马氏链在其上是f-指数遍历的.     

Markov Chain Approximations to Nonsymmetric Diffusions with Bounded Coefficients

We consider a certain class of nonsymmetric Markov chains and obtain heat kernel bounds and parabolic Harnack inequalities. Using the heat kernel estimates, we establish a sufficient condition for the family of Markov chains to converge to nonsymmetric diffusions. As an application, we approximate nonsymmetric diffusions in divergence form with bounded coefficients by nonsymmetric Markov chains. This extends the results by Stroock and Zheng to the nonsymmetric divergence forms. © 2012 Wiley Periodicals, Inc.     

Moderate deviations for Markov chains with atom

We obtain in this paper moderate deviations for functional empirical processes of general state space valued Markov chains with atom under weak conditions: a tail condition on the first time of return to the atom, and usual conditions on the class of functions. Our proofs rely on the regeneration method and sharp conditions issued of moderate deviations of independent random variables. We prove our result in the nonseparable case for additive and unbounded functionals of Markov chains, extending the work of de Acosta and Chen (J. Theoret. Probab. (1998) 75–110) and Wu (Ann. Probab. (1995) 420–445). One may regard it as the analog for the Markov chains of the beautiful characterization of moderate deviations for i.i.d. case of Ledoux 1992. Some applications to Markov chains with a countable state space are considered.     

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In this paper, we mainly studied the limit properties for the countable nonhomogeneous Markov chains. We established some limit properties for the functions of the countable nonhomogeneous Markov chains with variables under the convergence in the sense, which extended the similar conclusions for the functions with two variables. At last, as a corollary, we given the similar result in the homogeneous Markov stock market.     

Estimating Joint Distributions of Markov Chains

Suppose we observe a stationary Markov chain with unknown transition distribution. The empirical estimator for the expectation of a function of two successive observations is known to be efficient. For reversible Markov chains, an appropriate symmetrization is efficient. For functions of more than two arguments, these estimators cease to be efficient. We determine the influence function of efficient estimators of expectations of functions of several observations, both for completely unknown and for reversible Markov chains. We construct simple efficient estimators in both cases.     

关于渐近循环马氏链泛函的强大数定律

研究了一类非齐次马氏链———渐近循环马氏链泛函的强大数定律,首先引出了渐近循环马氏链的概念,然后给出了若干引理.利用了渐近循环马氏链关于状态序偶出现频率的强大数定理给出并证明了关于渐近循环马氏链泛函的强大数定律,所得定理作为推论可得到已有的结果.     

状态可数的马氏环境中马氏链函数的强大数定律

讨论了马氏双链与随机环境中马氏链的关系．在此基础上，研究了具有离散参量的马氏环境中马氏链函数的强大数定律，并且给出了直接加于链和过程样本函数上的充分条件．     

Comparison of Three Web Search Algorithms

In this paper we discuss three important kinds of Markov chains used in Web search algorithms-the maximal irreducible Markov chain, the miuimal irreducible Markov chain and the middle irreducible Markov chain, We discuss the stationary distributions, the convergence rates and the Maclaurin series of the stationary distributions of the three kinds of Markov chains. Among other things, our results show that the maximal and minimal Markov chains have the same stationary distribution and that the stationary distribution of the middle Markov chain reflects the real Web structure more objectively. Our results also prove that the maximal and middle Markov chains have the same convergence rate and that the maximal Markov chain converges faster than the minimal Markov chain when the damping factor α 〉1/√2.     

On the Critical Dimension and AC Entropy for Markov Odometers

Markov odometers are natural models for non-homogeneous Markov chains, and are natural generalisations of infinite product measures. We show how to calculate the critical dimension of these measures: this is an invariant which describes the asymptotic growth rate of sums of Radon-Nikodym derivatives. This interesting invariant appears to give a kind of entropy for non-singular odometer actions. The techniques require a law of large numbers for inhomogeneous Markov chains.     

On the Critical Dimension and AC Entropy for Markov Odometers

Markov odometers are natural models for non-homogeneous Markov chains, and are natural generalisations of infinite product measures. We show how to calculate the critical dimension of these measures: this is an invariant which describes the asymptotic growth rate of sums of Radon-Nikodym derivatives. This interesting invariant appears to give a kind of entropy for non-singular odometer actions. The techniques require a law of large numbers for inhomogeneous Markov chains.