负相关样本平滑移动过程的矩完全收敛性(英文)

本文研究了负相关样本平滑移动过程Xk=∑∞i=-∞ai+kYi的矩完全收敛性,这里{Yi,-∞相似文献   

负相关随机变量加权和的强定律(英文)

在本文中我们讨论了不同分布负相关随机变量加权和的强定律.在一个有限矩生成函数的条件下,一些有关负相关随机变量加权和的强定律被获得.这些结果推广了Soo HakSung[4]关于独立同分布随机变量的相应结论.我们的结果也概括了Mi Hwa Ko和Tae SungKim[7]获得的相关结论,同时使得Nili Sani H R和Bozorgnia A[9]所取得的结果更加形象.     

自相似马氏过程的Hausdorff维数(英文)

本文讨论了取值于 Rd的随机过程 Xt=( X1 ( t) ,X2 ( t) ,… ,XN( t) ) ,并且在一定条件下获得了 Xt的像集和图集的 Hausdorff维数 .这里 Xi( t) ,t∈ R 是独立的取值于 Rdi 的αi-自相似马氏过程 ,并且 ∑Ni=1 di=d.     

带迁入的分枝粒子系统的波动极限

本文研究了一个带迁入的对称稳定粒子系统，对此系统作时间和空间的重新标度，得到了重新标度过程的一个大数定律，证明了重新标度过程的波动极限是Ｏｒｎｓｔｅｉｎ－Ｕｈｌｅｎｂｅｃｋ超过程．     

随机环境中马氏链的平稳分布(英文)

本文引入了随机环境中马氏链平稳分布的概念. 在合适的条件下, 给出了随机环境中马氏链的平稳分布存在的一些充分条件. 特别地, 讨论了Cogburn链的平稳分布存在性问题. 同时, 构造了一个随机环境中马氏链的例子, 它的平稳分布是存在的.     

多类型粒子模型的图表示

本文利用图表示法构造出一类具有有限程的变相速率和不同扩散速率的同类型粒子模型,刻划出了该粒子模型的演化规律。     

负相关随机变量序列的对数律

在本文中,首先我们得到了负相关(ND)随机变量序列的指数不等式和矩不等式,然后运用这些不等式讨论了ND序列的对数律.结果,我们将独立情形下的对数律推广到ND序列情形下依然成立.     

关于一类非平衡交互作用粒子系统的相变

本文利用一维格点上非平衡Glauber＋Kawasaki过程所对应的Hgdrodynamic宏观方程，刻画了过程何时从一非渐近稳定态开始分离，该非渐近稳定态对应于一具有均值为常数的乘积测度，证明了时间标度在一定范围时，过程仍逗留在该非渐近稳定态．而时间标度超出该范围时，过程向渐近稳定态分叉，即系统发生相变．     

学习理论中基于负相关序列的样本误差估计

给定数据(x1,y1),(x2,y2),…,(xm,ym),考虑一般的损失函数ψ(y-f(x))下,当ψ(z)连续及ξ1=ψ(y1-f(x1)),ξ2=ψ(y2-f(x2)),…,ξm=ψ(ym-f(xm))是一个负相关序列时,本文研究了样本误差估计问题.     

一类抽球模型中两两(或相互)独立的条件及其模型构建

以一类抽球模型中由两两独立不能推出相互独立为基础,导出只由单色球和全色球构成的抽球模型中,抽到的球上的颜色两两独立的充要条件;然后得到并为必然事件的n个随机事件相互独立一个必要条件,并构建抽球模型中抽到的球上的颜色相互独立的球色彩结构.     

Ergodicity of Particle Systems

We study shift ergodicity, mixing, and related problems for invariant measures of interacting particle systems. The models we consider here include ferromagnetic stochastic Ising models, voter models, contact processes, exclusion processes, three-opinion noisy biased voter models, multi-opinion voter models, etc. Our results answer some questions for these models. One of the main techniques involved is a duality argument.     

Limits of One-dimensional Interacting Particle Systems with Two-scale Interaction*

This paper characterizes the limits of a large system of interacting particles distributed on the real line. The interaction occurring among neighbors involves two kinds of independent actions with different rates. This system is a generalization of the voter process, of which each particle is of type A or a. Under suitable scaling, the local proportion functions of A particles converge to continuous functions which solve a class of stochastic partial differential equations driven by Fisher-Wrig...     

Convergence of Empirical Processes for Interacting Particle Systems with Applications to Nonlinear Filtering

In this paper, we investigate the convergence of empirical processes for a class of interacting particle numerical schemes arising in biology, genetic algorithms and advanced signal processing. The Glivenko–Cantelli and Donsker theorems presented in this work extend the corresponding statements in the classical theory and apply to a class of genetic type particle numerical schemes of the nonlinear filtering equation.     

Feynman-Kac Particle Integration with Geometric Interacting Jumps

This article is concerned with the design and analysis of discrete time Feynman-Kac particle integration models with geometric interacting jump processes. We analyze two general types of model, corresponding to whether the reference process is in continuous or discrete time. For the former, we consider discrete generation particle models defined by arbitrarily fine time mesh approximations of the Feynman-Kac models with continuous time path integrals. For the latter, we assume that the discrete process is observed at integer times and we design new approximation models with geometric interacting jumps in terms of a sequence of intermediate time steps between the integers. In both situations, we provide nonasymptotic bias and variance theorems w.r.t. the time step and the size of the system, yielding what appear to be the first results of this type for this class of Feynman-Kac particle integration models. We also discuss uniform convergence estimates w.r.t. the time horizon. Our approach is based on an original semigroup analysis with first order decompositions of the fluctuation errors.     

Limit Processes for Age-Dependent Branching Particle Systems

We consider systems of spatially distributed branching particles in R ^d . The particle lifelengths are of general form, hence the time propagation of the system is typically not Markov. A natural time-space-mass scaling is applied to a sequence of particle systems and we derive limit results for the corresponding sequence of measure-valued processes. The limit is identified as the projection on R ^d of a superprocess in R ₊×R ^d . The additive functional characterizing the superprocess is the scaling limit of certain point processes, which count generations along a line of descent for the branching particles.     

Finite and Infinite Systems of Interacting Diffusions: Cluster Formation and Universality Properties

We study some aspects of the relationship between the long time behaviour of systems with a finite but large number of components and their idealizations with countably many components. The following class of models is considered in detail, which contains examples occuring in population growth and population genetic models.     

Dual Families of Interacting Particle Systems on Graphs

A simple condition for IPS (Interacting Particle Systems) with nearest neighbor interactions to be self-dual is given. It follows that any IPS with the contact transition and no spontaneous birth is self-dual. It is shown that families of IPS exist in which every IPS is dual to every other, and such that for every pair of IPS, one is a thinning of the other. Further, all such IPS have the same form for an equilibrium distribution when expressed in terms of survival probabilities. Convergence results from a wide class of initial infinite measures follow.     

Iterative Methods for Queuing Systems with Batch Arrivals and Negative Customers

In this paper, we are interested in solving the stationary probability distributions of Markovian queuing systems having batch arrivals and negative customers by using the Preconditioned Conjugate Gradient Squared (PCGS) method. The preconditioner is constructed by exploiting the near-Toeplitz structure of the generator matrix of the system. We proved that under some mild conditions the preconditioned linear systems have singular values clustered around one when the size of the queue tends to infinity. Numerical results indicated that the convergence rate of the proposed method is very fast.     

Rate of Convergence of a Stochastic Particle System for the Smoluchowski Coagulation Equation

By continuing the probabilistic approach of Deaconu et al. (2001), we derive a stochastic particle approximation for the Smoluchowski coagulation equations. A convergence result for this model is obtained. Under quite stringent hypothesis we obtain a central limit theorem associated with our convergence. In spite of these restrictive technical assumptions, the rate of convergence result is interesting because it is the first obtained in this direction and seems to hold numerically under weaker hypothesis. This result answers a question closely connected to the Open Problem 16 formulated by Aldous (1999).