U-统计量的几乎处处中心极限定理

本文得到了U-统计量的几乎处处中心极限定理(ASCLT).在EX1=0,EX21=1下,Berkes等[7]在一定条件下获得了i.i.d.随机变量序列部分和的函数型ASCLT,本文在同样的条件下取得了类似的结果.     

Almost Sure Central Limit Theorems for Heavily Trimmed Sums

We obtain an almost sure central limit theorem (ASCLT) for heavily trimmed sums. We also prove a function-typed ASCLT under the same conditions that assure measurable functions to satisfy the ASCLT for the partial sums of i.i.d, random variables with E X1 = 0, EX1^2 = 1.     

Almost sure central limit theorems for random functions

Let {Xn,-∞< n <∞} be a sequence of independent identically distributed random variables with EX1 = 0, EX12 = 1 and let Sn =∑k=1∞Xk, and Tn = Tn(X1,…,Xn) be a random function such that Tn = ASn Rn, where supn E|Rn| <∞and Rn = o(n~(1/2)) a.s., or Rn = O(n1/2-2γ) a.s., 0 <γ< 1/8. In this paper, we prove the almost sure central limit theorem (ASCLT) and the function-typed almost sure central limit theorem (FASCLT) for the random function Tn. As a consequence, it can be shown that ASCLT and FASCLT also hold for U-statistics, Von-Mises statistics, linear processes, moving average processes, error variance estimates in linear models, power sums, product-limit estimators of a continuous distribution, product-limit estimators of a quantile function, etc.     

一类统计量的强大数律和重对数律的精确极限性质

设{Xn,n≥1}是独立同分布随机变量序列,EX1=0,EX12=1.设Sn=n∑i=1Xi,Tn=Tn(X1,…,Xn)是随机函数且Tn=Sn+Rn.本文证明在E|Rn|2∨r《∞或E|Rn|《∞下,对随机函数Tn成立着Baum-Katz强大数律和重对数律的精确极限性质的一般结果.由此作为推论,对U-统计量,Von-Mises统计量,线性过程,移动平均过程,线性模型中误差方差估计和功率和等在适当矩条件下均可写出Baum-Katz强大数律和重对数律的精确极限性质.     

平稳正态序列超过数点过程与部分和的渐近联合分布

{Xi}为平稳正态序列,具有EX1=0,EX12=1,ρn=EX1Xn 1.对于水平un= ,记在 的条件下,得到了Nn(B)与Sn的渐近联合分布,同时也给出了极值与Sn的渐近联合分布.     

An almost sure central limit theorem for self-normalized weighted sums

Let X, X1 , X2 , ··· be a sequence of nondegenerate i.i.d. random variables with zero means, which is in the domain of attraction of the normal law. Let {a ni , 1≤i≤n, n≥1} be an array of real numbers with some suitable conditions. In this paper, we show that a central limit theorem for self-normalized weighted sums holds. We also deduce a version of ASCLT for self-normalized weighted sums.     

һ��ǿ����������ļ��޶����ע��

本文在{ξi}为强混合样本,{ani}是实三角阵列下,得到了一个新的关于线性和n∑i=1aniξi的中心极限定理.并利用该中心极限定理,进一步建立了线性过程部分和的中心极限定理.     

距离空间上的几乎处处中心极限定理

该文得到了关于一般可分距离空间上独立随机元序列的几乎处处中心极限定理(almost sure central limit theory, 简记为ASCLT). 作为应用, 该文给出了取值于可分Banach空间上随机元序列以及一类随机场序列满足ASCLT的充分条件,最后给出了关于多维随机变量序列极值的ASCLT.     

时间模上奇异m-点边值问题正解的存在性

运用Gatica,Oliker和Waltman锥上的不动点定理,在映射是减的条件下讨论时间模上的二阶非线性动力学方程m-点边值问题uΔΔ(t)+f(t,u(t))=0,t∈[0,1]Tu(0)=0,u(1)=∑m-2i=1αiu(ξi)正解的存在性.其中ξi∈(0,1)T,0<ξ1<ξ2<…<ξm-2<1,αi>0,0<∑m-2i=1αi 1.f(t,u)在u=0,t=0,u=∞是奇异的.     

一类Φ-Laplacian多点边值问题的可解性

获得了一类Φ-Laplacian多点边值问题((u′) )′=f (t,u,u′) ,0 相似文献   

The Intersective ASCLT

Abstract

In a recent work of the second named author on the Almost Sure Central Limit Theorem (ASCLT), we showed the usefulness of the concept of quasi-orthogonal system of random variables introduced by Bellman and later developed by Kac, Salem and Zygmund. In this paper, we propose an optimal formulation of the ASCLT again by using this idea and new correlation inequalities for sums of independent random variables. We also introduce and develop the notion of “intersective ASCLT” by proving some new results generalizing and improving substancially the classical formulation of the ASCLT. Essential tools for this approach are correlation inequalities recently developed by the first named author and some extensions of these ones obtained in the present paper.     

Weighted Limit Theorems for Continuous-Time Vector Martingales with Explosive and Mixed Growth

In this article, we establish the almost-sure central limit theorem (ASCLT) for a quasi-left continuous vector martingale with explosive and mixed (regular and explosive) growth. We also prove a quadratic extension and establish several new central limit theorems associated with the obtained ASCLT. Finally, we study the problem of parameter estimation in the particular case of multidimensional diffusion processes, which illustrates in a concrete manner the use of our results.     

A note on the ASCLT for triangular arrays of random variables with an extension to U-statistics

In this paper, we obtain an almost sure central limit theorem for products of independent sums of positive random variables. An extension of the result gives an ASCLT for the U-statistics.     

On the Almost Sure Central Limit Theorem for a Class of Z d -Actions

As an extension of earlier papers on stationary sequences, a concept of weak dependence for strictly stationary random fields is introduced in terms of so-called homoclinic transformations. Under assumptions made within the framework of this concept a form of the almost sure central limit theorem (ASCLT) is established for random fields arising from a class of algebraic Z ^d -actions on compact abelian groups. As an auxillary result, the central limit theorem is proved via Ch. Stein's method. The next stage of the proof includes some estimates which are specific for ASCLT. Both steps are based on making use of homoclinic transformations.     

Systèmes quasi-orthogonaux et théorème central limite presque sur

We prove, in the case of irrational rotations, the existence of a generalized moment version of the Almost Sure Central Limit Theorem (ASCLT), with a speed of convergence. In our strategy, we use the notion of quasi-orthogonal system, and purpose a Gaussian randomization technic, new at least in this context, which should also permit to be able to treat problems of comparable nature.     

Positive Periodic Solution of a Periodic Cooperative Model with State Dependent Delays

By using the continuation theorem of coincidence degree theory, sufficient conditions are obtained for the existence of positive periodic solution for the periodic cooperative system with state dependent delays where r i , a i , c i , i = 1, 2 are positive continuous y -periodic functions, b i , i = 1, 2 are nonnegative continuous y -periodic functions, and ij , i = 1, 2; j = 1, 2, 3 are nonnegative continuous functions and y -periodic with respect to their first argument.     

NA误差下部分线性模型的经验似然推断

对于部分线性模型yi=βxi+g(ti)+ei,1≤i≤n,这里(xi,ti)是固定设计点,g是未知函数,ei是负相协(NA)随机误差,给出了回归系数的经验似然比统计量,并讨论了似然比统计量的极限分布,可构造参数的经验似然置信区间.