非平稳NA序列部分和的精确渐近性

本文探讨了非平稳NA序列部分和的精确渐近性．以前的文献在讨论NA序列此类极限性质时都附加有强平稳条件的限制,这必然会给一些问题的研究带来不便．周知,非平稳NA序列在许多实际问题中是大量存在的,所以解除强平稳条件的束缚具有较大的理论和实际意义,这正是本文的目的之所在,同时本文也将已有的一些结果包含成为特殊情形．     

强平稳LPQD序列更新过程的渐近正态性

本文讨论了强平稳LPQD随机变量列更新过程的渐近正态性问题.     

一类Gauss序列极值的极限律

本文讨论一类非平稳Gauss序列的极值．利用点过程收敛定理得到多水平超过的点过程的收敛性,同时得到在不相交区间上最大值的联合渐近分布,第k个最大值的渐近分布以及前r个极值的联合渐近状态．     

平稳过程条件密度的双重核估计

本文在样本序列为平稳、φ-混合情形下研究了赵林城和刘志军提出的条件密度f(y|x)的双重核估计fn(y|x)的逐点强相合性和渐近正态性。我们对混合系数φ的限制是很弱的。     

含趋势项强相依非平稳序列的两个重要分布

{ηn}为平稳标准化正态序列,相关系数r|t-j|=Cov(ηu,ηj),若rnlogn→∞时,Leadbetter[1]等得到了序列最大值的渐近分布.本文考虑非平稳带有趋势项序列{ηn},得到了序列最大值的渐近分布和最大值与部分和的联合渐近分布.     

强混合序列的一类中心极限定理及其在回归模型中的应用[英文]

本文研究了强混合序列加权和的中心极限定理, 同时也给出了强混合序列线性过程部分和的中心极限定理. 作为应用,我们利用所得结果, 证明了固定设计回归模型中一类加权函数估计的渐近正态性.     

强混合序列的一类中心极限定理及其在回归模型中的应用(英文)

本文研究强混合序列加权和的中心极限定理,同时也给出强混合序列线性过程部分和的中心极限定理.作为应用,利用所得结果,证明固定设计回归模型中一类加权函数估计的渐近正态性.     

NA序列部分和的完全性收敛性

本文讨论了非平稳ＮＡ随机变量序列部分和的完全收敛性,获得了一般形式的完全收敛速度与矩条件之间的等价关系,其结果与独立情形一致,从而证实了ＮＡ序列与独立序列有着极为类似的完全收敛性。     

ARCH(p)模型样本均值与样本自相关函数的渐近正态性

利用严平稳m步相依序列中心极限定理证明了ARCH(p)模型样本均值与样本自相关函数的渐近正态性质.     

非平稳ND序列部分和的精确渐近性

利用中心极限定理和概率不等式,本文建立了非平稳ND序列部分和的精确渐近性,得到了与非平稳NA序列情形下相同的结果.     

Convergence of nonstationary cascade algorithms

Summary. A nonstationary multiresolution of is generated by a sequence of scaling functions We consider that is the solution of the nonstationary refinement equations where is finitely supported for each k and M is a dilation matrix. We study various forms of convergence in of the corresponding nonstationary cascade algorithm as k or n tends to It is assumed that there is a stationary refinement equation at with filter sequence h and that The results show that the convergence of the nonstationary cascade algorithm is determined by the spectral properties of the transition operator associated with h. Received September 19, 1997 / Revised version received May 22, 1998 / Published online August 19, 1999     

Forecast horizon in nonstationary Markov decision problems

The paper extends the concept of decision and forecast horizons from classes of stationary to classes of nonstationary Markov decision problems. The horizons are explicitly obtained for a family of inventory models. The family is indexed by nonstationary Markov chains and deterministic sequences. For the proof only reference to simlier work on the stationary case is made.     

独立与NA列部分和的精致渐近性

令{X,Xi:i≥1)为属于非退化稳定分布一般吸引场的独立同分布随机变量列,Sn=∑i=1nXi.本文对十分广泛的拟权函数和边界函数得到了Sn的精致渐近的结果和正态吸引场强平稳NA列部分和的精致渐近的结果,改进并推广了Wang等的结果,从而使此前关于独立列和NA列部分和精致渐近性方面的许多经典的和最新的结果都可以包括在本文的框架之内.     

NA序列的重对数矩收敛的精确渐近性

假设{X_n,n≥1}为一列严平稳的NA随机变量,期望为零,方差有限.设S_n=∑_(i=1)~n∑X_i,M_n=max_(1≤i≤n)|S_i|.在适当的条件下,得到了一类NA序列部分和部分和最大值重对数矩收敛的精确渐近性.     

Moment inequalities and weak convergence for negatively associated sequences

A probability inequality for S_n and somepth moment (p⩾2) inequalities for |S_n| and max 1⩽k⩽n | S_k| are established. Here S_n is the partial sum of a negatively associated sequence. Based on these inequalities, a weak invariance principle for strictly stationary negatively associated sequences is proved under some general conditions. Project supported by the National Natural Science Foundation of China, the Doctoral Program Foundation of the State Education Commission of China and the High Eductional Natural Science Foundation of Guangdong Province.     

��ƽ��ND���в��ֺ͵ľ�ȷ������

In this paper, by using central limit theorem of ND sequences and probability inequality, the precise asymptotics for partial sums of nonstationary ND sequences is investigated, and the same results with it under that of NA sequences are obtained.     

A central limit theorem for stationary random fields

Summary. We prove a central limit theorem for strictly stationary random fields under a projective assumption. Our criterion is similar to projective criteria for stationary sequences derived from Gordin's theorem about approximating martingales. However our approach is completely different, for we establish our result by adapting Lindeberg's method. The criterion that it provides is weaker than martingale-type conditions, and moreover we obtain as a straightforward consequence, central limit theorems for α-mixing or φ-mixing random fields. Received: 19 February 1997 / In revised form: 2 September 1997     

基于双AR(p)模型的股价分析及其实证研究

在双AR(p)模型的基础上,选取了具有代表性的沪深300指数,并对其部分股市收盘价序列进行了平稳化处理,研究了近期中国股市的股价波动.在双.AR(p)模型严平稳条件下进行了模型诊断,最后通过动态预测得出双AR(p)模型可用于股价预测的结论.     

Hölder convergence of autoregression residuals partial sum processes

We investigate polygonal line processes constructed from residuals of the AR(1) model in the framework of Hölder spaces. Both stationary and nonstationary cases are considered.