On the Central Limit Theorem and Its Weak Invariance Principle for Strongly Mixing Sequences with Values in a Hilbert Space via Martingale Approximation

In this paper we not only prove an extension to Hilbert spaces of a sharp central limit theorem for strongly real-valued mixing sequences, but also slightly improve it. The proof is mainly based on the Bernstein blocking technique and approximations by martingale differences. Moreover, we derive also the corresponding functional central limit theorem.     

An Almost Sure Central Limit Theorem for Weighted Sums of Mixing Sequences

In this paper, we prove an almost sure central limit theorem for weightedsums of mixing sequences of random variables without stationary assumptions. We nolonger restrict to logarithmic averages, but allow rather arbitrary weight sequences.This extends the earlier work on mixing random variables.     

A Non-Uniform Estimate in the Central Limit Theorem for Sequences of Strongly Additive Functions

The value distribution of a normalised sequence of strongly additive arithmetic functions

NA序列中心极限定理的收敛速度

本文对NA（NegativelyAssociated）序列建立了中心极限定理的一致收敛速度，只要其三阶矩有限及描述NA序列协方差结构的一个系数u（n）被负指数序列所控制，而无需平稳性便获得了其收敛速度O（n(-1/2)logn）。     

ψ-混合样本下含附加信息时条件分位数估计的渐近性质

本文利用经验似然方法构造了含附加信息时条件分位数的一类估计,并证明了估计的渐近正态性且渐近方差不大于通常核估计的渐近方差.     

Banach空间上的强混合算子

1999年,L．B．Gonzalez 证明了任意无限维可分 Banach 空间上存在拓扑传递的有界线性算子．这个结果肯定地回答了 S．Rolewicz 提出的问题．本文证明了由 L．B．Gonzalez 所给出的算子实际上是强混合的,同时,对加权移位算子的混合性利用权序列进行了刻划并指出任意无限维可分 Hilbert 空间上存在弱混合而非强混合的有界线性算子．     

On Normal Approximation for Strongly Mixing Random Variables

In this paper, we estimate the difference , where Z _n is the sum of n centered and normalized random variables (without the stationarity assumption) satisfying the strong mixing condition, N is a standard normal random variable, and h:ℝ→ℝ is a Lipschitz function. In particular cases, the obtained upper bounds are of order O(n ^−1/2). The research was partially supported by the Lithuanian State Science and Studies Foundation, grant No. T-10/06.     

Strongly Mixing Sequences of Measure Preserving Transformations

We call a sequence (T _n ) of measure preserving transformations strongly mixing if tends to P(A)P(B) for arbitrary measurable A, B. We investigate whether one can pass to a suitable subsequence such that almost surely for all (or "many") integrable f.     

On a theorem of gordin

M. I. Gordin proved a central limit theorem for some strictly stationary strongly mixing random sequences without the usual assumption of finite second moments. In this note we show that in that theorem, his assumption of a mixing rate (for the strong mixing condition) cannot be altogether omitted     

Mixing Limit Theorems for Ergodic Transformations

We show that distributional and weak functional limit theorems for ergodic processes often hold for arbitrary absolutely continuous initial distributions. This principle is illustrated in the setup of ergodic sums, renewal-theoretic variables, and hitting times for ergodic measure preserving transformations.     

A Central Limit Theorem for Non-stationary Strongly Mixing Random Fields

In this paper we extend a central limit theorem of Peligrad for uniformly strong mixing random fields satisfying the Lindeberg condition in the absence of stationarity property. More precisely, we study the asymptotic normality of the partial sums of uniformly \(\alpha \)-mixing non-stationary random fields satisfying the Lindeberg condition, in the presence of an extra dependence assumption involving maximal correlations.     

Rates in the Empirical Central Limit Theorem for Stationary Weakly Dependent Random Fields

A weak dependence condition is derived as the natural generalization to random fields on notions developed in Doukhan and Louhichi (1999). Examples of such weakly dependent fields are defined. In the context of a weak dependence coefficient series with arithmetic or geometric decay, we give explicit bounds in Prohorov metric for the convergence in the empirical central limit theorem. For random fields indexed by &Zopf ^d , in the geometric decay case, rates have the form n ^−1/(8d+24) L(n), where L(n) is a power of log(n). This revised version was published online in June 2006 with corrections to the Cover Date.     

混沌与拓扑强混合

讨论了拓扑强混合、Li—Yorke混沌和修改的Devaney混沌三者之间的关系,我们得到:Li—Yorke混沌与修改的Devaney混沌无蕴涵关系;Li—Yorke混沌和修改的Devaney混沌均不能蕴涵着拓扑强混合,这解决了文献[1]中提出的两个问题.     

Banach空间上强混合的C0-半群

证明了每个可分无限维复Banach空间上都存在一个强混合的Co-半群,在加权函数空间上给出了转移半群是强混合的一个充要条件.     

关于任意随机变量序列的强极限定理的一个注记

主要说明两两NQD随机变量序列的一些收敛性质是任意随机变量序列的强极限定理的推论.     

Multivariate Variational Inequalities and the Central Limit Theorem

Multivariate variational inequalities are obtained in terms of thew-functions and the trace of a Fisher-type information matrix. In consequence of these inequalities, the multivariate central limit theorem arises in the sense of the total variation.     

随机Volterra方程的中心极限定理

在本文中,我们研究一类随机Volterra方程,它包含了分数布朗运动驱动的随机微分方程等模型.我们利用Itō (1979)建立的一个极大不等式,在连续函数空间中关于一致收敛拓扑,建立了中心极限定理.     

非齐次马氏链的中心极限定理

本文将针对非齐次马氏链的转移矩阵列在Ces`aro收敛意义下,利用鞅的中心极限定理证明一个不同于Dobrushin结果的非齐次马氏链的中心极限定理。     

Empirical Polygon Simulation and Central Limit Theorems for the Homogenous Poisson Line Process

For the Poisson line process the empirical polygon is defined thanks to ergodicity and laws of large numbers for some characteristics, such as the number of edges, the perimeter, the area, etc... One also has, still thanks to the ergodicity of the Poisson line process, a canonical relation between this empirical polygon and the polygon containing a given point. The aim of this paper is to provide numerical simulations for both methods: in a previous paper (Paroux, Advances in Applied Probability, 30:640–656, 1998) one of the authors proved central limit theorems for some geometrical quantities associated with this empirical Poisson polygon, we provide numerical simulations for this phenomenon which generates billions of polygons at a small computational cost. We also give another direct simulation of the polygon containing the origin, which enables us to give further values for empirical moments of some geometrical quantities than the ones that were known or computed in the litterature. This work was partially supported by the PSMN at ENS-Lyon.     

非线性递归数列的极限

探讨了形如Fn+p=pΣ1=1α1Fbin+i,≥1的非线性递归数列{Fn)的极限问题,给出了在满足一定条件时,数列{Fn}极限存在且与初始值无关.