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．     

强相依高斯序列超过数点过程与部分和的联合渐近分布

（Ｘｎ）为标准化平稳高斯序列,ｐｎ＝ＥＸ１Ｘｎ＋１,Ｎｎ为Ｘ１,Ｘ２,…,Ｘｎ对水平ｕｎ＝ｘ／ａｎ＋ｂｎ的超过数形成的点过程,Ｍｎ＾（ｋ）为Ｘ１,Ｘ２,…,Ｘｎ的第ｋ个最大值,Ｓｎ＝（ｎ）∑（ｉ＝１）Ｘｉ,ｐｎｌｏｇｎ→ｒ∈（０,∞）时,得到Ｎｎ与Ｓｎ、Ｍｎ＾（ｋ）与Ｓｎ的联合渐近分布。     

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.     

强相依非平稳高斯序列超过数点过程与部分和的联合渐近分布

设{Xi}∞i=1是标准化强相依非平稳高斯序列,记Sn=∑Xi,σn=√var(Sn),Mktn为X1,X2,…,Xtn的第k个最大值,Ntn为X1,X2,…,Xtn对水平μn(x)的超过数形成的点过程,tn是-列单调增加的正整数列,在一定条件下得到Ntn与Sn/σn,Mktn与Sn/σn的联合渐近分布.     

一个除数问题的推广

本文推广了Ｒ．Ａ．Ｓｍｉｔｈ，Ｍ．Ｖ．Ｓｕｂｂａｒａｏ和Ｇ．Ｎｏｗａｋ所考虑的一个除数问题．令Ｓ＝｛（ａｉ，ｑｉ）｜ａｉ≤ｑｉ｝（ｒ≥３）．定义ｄ（ｎ；Ｓ）＝Σ（１）１，Σ（１）表示对满足ｎ＝ｍ１…ｍｒ，ｍｊ≡ａｊ（ｍｏｄｑｊ），ｊ＝１，２，…，ｒ的诸ｍｊ求和．我们求出了Σｎ≤ｘｄ（ｎ；Ｓ）的渐近公式，并得到了余项估计．     

基于Bootstrap的厚尾相依序列持久性变点检验

基于修正方差比率函数给出一种检验厚尾序列持久性变点的统计量.在无变点的假设下得到了统计量的渐近分布.为避免检验渐近分布中的厚尾指数,构造Bootstrap抽样方法来确定渐近分布的经验临界值.数值模拟研究结果说明修正方差比率统计量及Bootstrap抽样方法的有效性.     

随机删失下位置-刻度模型中的强相合与渐近正态估计

在删失分布未知的情形下,证明了所定义的位置─刻度模型中参数估计的强相合性与渐近正态性．在证明估计的渐近正态性时,使用了点过程鞅方法．     

论正定列的一种扩张

设１，ｒ１，ｒ２，．．．ｒｍ，ｘ，１，ｒ１，ｒ２．．．，ｒｍ，ｘ，ｙ，ｙ∈（ａ，ｂ），ａ，ｂ，１，ｒ１，ｒ２，．．．，ｒｍ。     

独立非同分布二元高斯三角阵最大值的渐近性及相关统计推断

考虑二元独立非同分布高斯随机向量三角阵列最大值分布的渐近性及相关统计推断.此高斯三角阵的第n列的第i个向量服从二元高斯分布,其相关系数为i/n的函数并单调连续.首先建立了此高斯三角阵最大值分布的一阶和二阶渐近展开式.其次,分析相关系数参数估计及估计量的渐近性质.最后,通过随机模拟说明了相关系数之参数估计的有效性,并将该二元非同分布三角阵列模型应用于实际数据,得到了满意的结果.     

C~r－局部线性化

本文在非定常系统中引入了半轴上的Ｃｒ－结构稳定和Ｃｒ－局部线性化的概念，并且得到，一致渐近稳定的线性系统具有Ｃｒ－结构稳定以及其零解的变分方程系具有一致渐近稳定的ｒ阶拟线性系统可Ｃｒ－局部线性化．     

Strong convergence of multivariate point processes of exceedances

We study the asymptotic behavior of vectors of point processes of exceedances of random thresholds based on a triangular scheme of random vectors. Multivariate maxima w.r.t. marginal ordering may be regarded as a special case. It is proven that strong convergence—that is convergence of distributions w.r.t. the variational distance—of such multivariate point processes holds if, and only if, strong convergence of multivariate maxima is valid. The limiting process of multivariate point processes of exceedances is built by a certain Poisson process. Auxiliary results concerning upper bounds on the variational distance between vectors of point processes are of interest in its own right.The author was supported by the Deutsche Forschungsgemeinschaft.     

Hidden Regular Variation, Second Order Regular Variation and Asymptotic Independence

We survey the related asymptotic properties of multivariate distributions; (i) asymptotic independence, (ii) hidden regular variation, and (iii) multivariate second order regular variation. Connections and implications are discussed. The point of view of convergence of measures is emphasized in formulations because we are interested in the concepts being coordinate system free, whenever possible.     

演化策略的全局收敛性

１．引言 进化算法（ＥＡ, Ｅｖｏｌｕｔｉｏｎａｒｙ Ａｌｇｏｒｉｔｈｍｓ）是近年来兴起的一类基于生物界的自然选择和自然遗传机制的计算方法,如遗传算法（ＧＡ, Ｇｅｎｅｔｉｃ Ａｌｇｏｒｉｔｈｍｓ）、演化策略（ＥＳ,Ｅｖｏｌｕｔｉｏｎ Ｓｔｒａｔｅｇｉｅｓ）和进化规划（ＥＰ, Ｅｖｏｌｕｔｉｏｎａｒｙ Ｐｒｏｇｒａｍｍｉｎｇ）等方法．这类算法的主要优点在于其本质上的并行性、广泛的可应用性和算法的高度稳健性、简明性与全局优化性［１,２］．目前,进化算法已被广泛地应用于计算机科学、工程技术、管理科学和社会科…     

Empirical processes indexed by smooth functions

In this paper we derive a general invariance principle for empirical processes indexed by smooth functions. The method is applied to prove bounds for the convergence of the empirical distributions which might be useful to verify asymptotic normality of smooth statistical functionals. As one further application we get the convergence of the so-called empirical characteristic function process.     

Subcritical, Critical and Supercritical Size Distributions in Random Coagulation-Fragmentation Processes

We consider the asymptotic probability distribution coagula-tion-fragmentation process in the thermodynamic limit of the size of a reversible random We prove that the distributions of small, medium and the largest clusters converge to Gaussian, Poisson and 0-1 distributions in the supercritical stage （post-gelation）, respectively. We show also that the mutually dependent distributions of clusters will become independent after the occurrence of a gelation transition. Furthermore, it is proved that all the number distributions of clusters are mutually independent at the critical stage （gelation）, but the distributions of medium and the largest clusters are mutually dependent with positive correlation coefficient in the supercritical stage. When the fragmentation strength goes to zero, there will exist only two types of clusters in the process, one type consists of the smallest clusters, the other is the largest one which has a size nearly equal to the volume （total number of units）.     

同时具有点和区间半径序列收敛性的免导迭代法的进一步讨论

1 引 言 传统的求零点的迭代法只讨论迭代序列{xn}的收敛阶,近年来,G.Alefeld和F.A.Po-tra研究了含零点的区间半径序列的收敛性[2][3],而我们提出了同时具有点和区间半径序列均平方收敛的免导迭代法[1],即当n充分大时,序列{xn}和含零点区间的半径序列{(bn-an)}都是平方收敛的.通过进一步的分析,我们发现,文[1]中的结果仍可改进,并且,不需     

Extreme value analysis for the sample autocovariance matrices of heavy-tailed multivariate time series

We provide some asymptotic theory for the largest eigenvalues of a sample covariance matrix of a p-dimensional time series where the dimension p = p _n converges to infinity when the sample size n increases. We give a short overview of the literature on the topic both in the light- and heavy-tailed cases when the data have finite (infinite) fourth moment, respectively. Our main focus is on the heavy-tailed case. In this case, one has a theory for the point process of the normalized eigenvalues of the sample covariance matrix in the iid case but also when rows and columns of the data are linearly dependent. We provide limit results for the weak convergence of these point processes to Poisson or cluster Poisson processes. Based on this convergence we can also derive the limit laws of various function als of the ordered eigenvalues such as the joint convergence of a finite number of the largest order statistics, the joint limit law of the largest eigenvalue and the trace, limit laws for successive ratios of ordered eigenvalues, etc. We also develop some limit theory for the singular values of the sample autocovariance matrices and their sums of squares. The theory is illustrated for simulated data and for the components of the S&P 500 stock index.     

The Generating Function for the Airy Point Process and a System of Coupled Painlevé II Equations

For a wide class of Hermitian random matrices, the limit distribution of the eigenvalues close to the largest one is governed by the Airy point process. In such ensembles, the limit distribution of the k th largest eigenvalue is given in terms of the Airy kernel Fredholm determinant or in terms of Tracy–Widom formulas involving solutions of the Painlevé II equation. Limit distributions for quantities involving two or more near‐extreme eigenvalues, such as the gap between the k th and the ℓth largest eigenvalue or the sum of the k largest eigenvalues, can be expressed in terms of Fredholm determinants of an Airy kernel with several discontinuities. We establish simple Tracy–Widom type expressions for these Fredholm determinants, which involve solutions to systems of coupled Painlevé II equations, and we investigate the asymptotic behavior of these solutions.     

Asymptotic behavior of posterior distributions for random processes under incorrect models

In this paper, the asymptotic behavior of posterior distributions on parameters contained in random processes is examined when the specified model for the densities is not necessarily correct. Uniform convergence of likelihood functions in some way is shown to be a sufficient condition for the posterior distributions to be asymptotically confined to a set (Theorem 1). For ergodic stationary Markov processes uniform convergence of likelihood functions is established by the ergodic theorem for Banach-valued stationary processes (Proposition 1). A sufficient condition for the uniform convergence is also shown for general random processes (Proposition 2). These results are used to analyze the asymptotic behavior of posterior distributions on parameters contained in linear systems under incorrect models (Example 1 and 2).