On the first birth and the last death in a generation in a multi-type Markov branching process

In a multi-type continuous time Markov branching process the asymptotic distribution of the first birth in and the last death (extinction) of the kth generation can be determined from the asymptotic behavior of the probability generating function of the vector Z(^k)(t), the size of the kth generation at time t, as t tends to zero or as t tends to infinity, respectively. Apart from an appropriate transformation of the time scale, for a large initial population the generations emerge according to an independent sum of compound multi-dimensional Poisson processes and become extinct like a vector of independent reversed Poisson processes. In the first birth case the results also hold for a multi-type Bellman-Harris process if the life span distributions are differentiable at zero.     

Second order limit theorems for the Markov branching process in random environments

In a Markov branching process with random environments, limiting fluctuations of the population size arise from the changing environment, which causes random variation of the ‘deterministic’ population prediction, and from the stochastic wobble around this ‘deterministic’ mean, which is apparent in the ordinary Markov branching process. If the random environment is generated by a suitable stationary process, the first variation typically swamps the second kind. In this paper, environmental processes are considered which, in contrast, lead to sampling and environmental fluctuation of comparable magnitude. The method makes little use either of stationarity or of the branching property, and is amenable to some generalization away from the Markov branching process.     

On the transition from a Markov chain to a continuous time process

Starting from a real-valued Markov chain X₀,X₁,…,X_n with stationary transition probabilities, a random element {Y(t);t[0, 1]} of the function space D[0, 1] is constructed by letting Y(k/n)=X_k, k= 0,1,…,n, and assuming Y (t) constant in between. Sample tightness criteria for sequences {Y(t);t[0,1]};_n of such random elements in D[0, 1] are then given in terms of the one-step transition probabilities of the underlying Markov chains. Applications are made to Galton-Watson branching processes.     

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本文利用构造鞅的方法, 研究了Cayley树图上奇偶马氏链场的强极限定理, 给出了Cayley树图上奇偶马氏链场关于状态和状态序偶出现频率的强大数定律, 推广了一个已知结果.     

二叉树上分枝马氏链的强大数定理

首先给出了在可列状态空间取值的二叉树上分枝马氏链定义的离散形式,然后建立了二叉树上分枝马氏链的若干强极限定理,最后研究了二叉树上有限状态分枝马氏链的强大数定理．     

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.     

Uniqueness and Extinction of Weighted Markov Branching Processes

This paper focuses on discussing some basic properties of the weighted Markov branching process which is a natural generalisation of the ordinary Markov branching process. The regularity and uniqueness criteria, which are very easy to verify, are firstly established. Some important characteristics regarding the hitting times of such structure are obtained. In particular, the closed forms for the mean extinction time and conditional mean extinction time are presented. The explosion behaviour of the process is investigated and then the mean explosion time is derived. The mean global holding time and the mean total survival time are also obtained. AMS 2000 Subject Classification Primary 60 J27; Secondary 60 J80     

On a Markov process generated by non-decreasing concave functions

A discrete-time Markov process on [0, ∞) is considered. The process is generated by selecting at each time, in an independent and stationary way, a concave non-decreasing function. Sufficient conditions for the existence of a unique stationary limiting distribution are given.     

弱相依随机序列的若干新结果(英文)

设{Xn,n≥1}为-混合序列. 利用随机变量的截尾方法和-混合序列的三级数定理,讨论了-混合序列的收敛性质,并且得到了-混合序列的一类强极限定理,这些结果推广了独立序列的相应结果.最后研究了-混合序列加权和的强稳定性.     

Bernoulli thinning of a Markov renewal process

A Bernoulli thinning of a Markov renewal process is investigated. The properties of the thinned process are considered and are related to the properties of the original process. The parameters, moments and equilibrium of the thinned process are determined in terms of the parameters defining the underlying Markov renewal process. Results are illustrated by examples. © 1998 John Wiley & Sons, Ltd.     

Local Times of Markov Processes Approximated by a Generalized Iterated Brownian Motion

Csáki et al.⁽⁵⁾ have given strong approximations of continuous additive functional of Brownian motion. We establish here an extension of these results for a large class of Markov processes.     

树指标马氏链的一个强极限定理

树指标随机过程已成为近年来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.研究给出了一类非齐次树上马氏链的一个强极限定理.     

Strong 0-discount optimal policies in a Markov decision process with a Borel state space

We consider a Markov decision process with a Borel state space, a countable action space, finite action sets, bounded rewards and a bounded transition density satisfying a simultaneous Doeblin condition. The existence of stationary strong 0-discount optimal polices is proved.Supported by NSF grant DMS-9404177.     

The square of a Gaussian Markov process and nonlinear prediction

An explicit formula is obtained for the nonlinear predictor of Y(t) = X(t)² − E(X(t)²), where X(t) is an N-ple Gaussian Markov process.     

Strong stationary duality for continuous-time Markov chains. Part I: Theory

LetX(t), 0t<, be an ergodic continuous-time Markov chain with finite or countably infinite state space. We construct astrong stationary dual chainX ^* whose first hitting times yield bounds on the convergence to stationarity forX. The development follows closely the discrete-time theory of Diaconis and Fill.^(2,3) However, for applicability it is important that we formulate our results in terms of infinitesimal rates, and this raises new issues.     

Uniform Asymptotic Expansion of Likelihood Ratio for Markov Dependent Observations

An asymptotic expansion of the logarithm of the likelihood ratio for Markov dependent observation is obtained. A functional limit theorem for the likelihood ratio is proved, which gives a way to study limiting distributions of the likelihood ratio based on stopping times, in particular, that of sequential probability ratio test.     

非齐次树上m阶非齐次马氏连的一类强极限定理

树指标随机过程已成为近年来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m阶非齐次马氏链的若干强极限定理.     

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.     

THE POINT PROCESS OF STATETRANSITIONS IN AREGULAR MARKOV CHAIN

1.IntroductionInreliabilitytheory,inordertocalculatethefailurefrequencyofarepairablesystem,Shily]firstintroducedandstudiedthetransitionfrequencybetweentwodisjointstatesetsforafiniteMarkovchainandavectorMarkovprocesswithfinitediscretestatespaceandobtainedageneralformulaoftransitionfrequency.Then,ontheconditionthatthegeneratormatrixofMarkovchainisuniformlybounded,Shi[8'9]againprovedthetransitionfrequencyformulaandobtainedthreeotherusefulformulas.Obviously,thepoint(orcalledcounting)processofsta…