任意随机序列关于非齐次马氏链的随机和的一类随机偏差定理

In this paper, the notion of limit random logarithmic likelihood ratio of stochastic sequence, as a measure of dissimilarity between the joint distribution on measure P and the Markov distribution on measure Q, is introduced. A class of random approximation theorems for arbitrary stochastic dominated sequence are obtained by using the tools of generating functions and the tailed-probability generating functions.     

绕积马氏链的中心极限定理

讨论了具有离散参数的绕积马氏链的中心极限定理,给出了加在过程样本函数上充分条件。得到了绕积马氏链的中心极限定理成立的充分条件.     

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??The local limit theorems for the minimum of a random walk with Markovian increments is given, with using Presman's factorization theory. This result implies the asymptotic behaviour of the survival probability for a critical branching process in Markovian depended random environment.     

一个随机偏差定理

设{Xn,n≥0}是可列非齐次马尔可夫链,Sn（i0,i1,…,im-1,ω）表示m元状态序组（i0,i1,…,im-1）在序列（X0,X1,…,Xm-1）,（X1,X2,…,Xm）,…,（Xn-1,Xn,…,Xn＋m-2）中出现的次数.本文给出了关于Sn（i0,i1,…,im-1,ω）的一个对任意可列非齐次马尔可夫链普遍成立的随机偏差定理,即用不等式表示的一个强极限定理.     

一个随机偏差定理

设{Xn,n≥0}是可列非齐次马尔可夫链,Sn(i0,i1,…,im-1,ω)表示m元状态序组(i0,i1,…,im-1)在序列(X0,X1,…,Xm-1),(X1,X2,…,Xm),…,(Xn-1,Xn,…,Xn+m-2)中出现的次数.本文给出了关于Sn(i0,i1,…,im-1,ω)的一个对任意可列非齐次马尔可夫链普遍成立的随机偏差定理,即用不等式表示的一个强极限定理.     

Central Limit Theorem for a Class of Nonhomogeneous Random Walks

A spatially nonhomogeneous random walk _t on the grid =^m X ⁿ is considered. Let _t ⁰ be a random walk homogeneous in time and space, and let _t be obtained from it by changing transition probabilities on the set A= X ⁿ, || < , so that the walk remains homogeneous only with respect to the subgroup ⁿ of the group . It is shown that if >m 2 or the drift is distinct from zero, then the central limit theorem holds for _t.     

关于马氏链强极限定理的一个新结论

本文的目的是要给出一个新形式的对任意可列非齐次马氏链普遍成立的强极限定理     

可列值随机变量序列的一个小偏差定理

本文得到了可列值随机变量序列的用不等式表示的强极限定理,即小偏差定理,包含了［１］的结果．［１］中研究的是相对于齐次Ｍａｒｋｏｖ 链的偏差,而本文允许非齐次的情形．     

一个关于马尔可夫链的极限定理

给出一个关于可列非齐次马尔可夫链M元状态序组出现频率的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.     

树上马氏链场的若干极限性质

该文引进广义Ｂｅｔｈｅ树和广义Ｃａｙｌｅｙ树的概念,并研究其上马氏链场关于状态和状态序偶出现频率的强极限定理,作为主要结果的推论,得到Ｂｅｔｈｅ树和Ｃａｙｌｅｙ树上马氏链场的ＳｈａｎｎｏｎＭｃＭｉｌｌａｎ定理．证明中采用了研究概率论强极限定理的一种新的方法．     

二重非齐次马氏链及其随机变换的若干强极限定理

利用鞅方法,给出二重非齐次马尔可夫链三元函数的几个强极限定理.作为特例,将赌博系统的随机变换概念推广到二重马氏链情形,得到二重马氏链随机选择与随机公平比的若干极限定理.     

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.     

Generalized Nonparametric Mixed Effects Models

Generalized linear mixed effects models (GLMM) provide useful tools for correlated and/or over-dispersed non-Gaussian data. This article considers generalized nonparametric mixed effects models (GNMM), which relax the rigid linear assumption on the conditional predictor in a GLMM. We use smoothing splines to model fixed effects. The random effects are general and may also contain stochastic processes corresponding to smoothing splines. We show how to construct smoothing spline ANOVA (SS ANOVA) decompositions for the predictor function. Components in a SS ANOVA decomposition have nice interpretations as main effects and interactions. Experimental design considerations help determine which components are fixed or random. We estimate all parameters and spline functions using stochastic approximation with Markov chain Monte Carlo (MCMC). As iteration increases we increase the MCMC sample size and decrease the step-size of the parameter update. This approach guarantees convergence of the estimates to the expected fixed points. We evaluate our methods through a simulation study.     

剖析马氏链平稳分布的讲解——谈《应用随机过程》教学

通过平稳分布在Google搜索技术中的应用角度讲解马氏链的平稳分布的概念,并在此基础上对应用随机过程的教学做了粗浅的探讨.     

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.     

广义Bethe树指标可列马氏链场关于广义随机选择系统的一类局部极限定理

研究任意广义Bethe树指标马尔可夫链场二元泛函关于广义随机选择系统的一类局部极限定理.作为推论得到了广义随机选择系统中任意Cayley树上状态频率和状态序偶的一类极限定理.证明中采用了一种研究马尔可夫链场的较新颖的分析方法.     

求解具有确定性线性不等式约束的有补偿随机规划问题的近似ε——容许方向法

1引言形如线性不等式确定性约束的有补偿随机规划问题     

任意随机序列关于二重非齐次马氏链的随机和的一类随机选择系统的随机逼近定理

本文引进任意随机变量序列随机极限对数似然比的概念,通过测度$pr$下任意相依随机序列联合分布与测度$qr$下二重非齐次马氏分布相比较,利用母函数与尾概率母函数工具研究任意受控随机序列之随机和在随机选择系统中的一类随机逼近定理.     

On the Number of Subgraphs of a Specified Form Embedded in a Random Graph

Let U ₁, U ₂,... be a sequence of i.i.d. random elements in R^d. For x>0, a graph G _n (x) may be formed by connecting with an edge each pair of points in that are separated by a distance no greater than x. The points of G _n (x) could represent the stations in a telecommunications network and the edge set the lines of communication that exist among them. Let be a collection of graphs on mn points having a specified form or structure, and let denote the number of subgraphs embedded in G _n (x) and contained in . It is shown that a SLLN, CLT and LIL for follow easily from the theory of U-statistics. In addition, a uniform (in x) SLLN is proved for collections that satisfy a certain monotonicity condition. Some applications are mentioned and the results of some simulations presented. The scaling constants appearing in the CLT are usually hard to obtain. These are worked out for some special cases.