The Invariance Principle for Linear Processes Generated by a Negatively Associated Sequence and Its Applications

In this paper, we obtain the invariance principle for linear processes generated by a negatively associated sequence.     

随机变量的负超可加相依及其应用

一个随机向量Ｘ＝（Ｘ１,Ｘ２,．．．,Ｘｍ）称为负超可加相依（ＮＳＤ）,如果对每个超可加函数Х,ＥХ（Ｘ１,Ｘ２,．．．,Ｘｍ）≥ＥХ（Ｙ１,Ｙ２,．．．,Ｙｍ）,其中Ｙ１,Ｙ２,．．．,Ｙｍ相互独立且对任意ｉ,Ｙｉ＝ｄＸｉ,本文研究了ＮＳＤ的基本性质,给出了ＮＳＤ判定的三个结构 定理,并且这些定理可用来证明许多著名的多元分布具有ＮＳＤ性质,本文还给出了ＮＡＤ的许多概率不等式。     

二元示数计算

所谓的二元示数是指用上一下四珠算盘,靠梁珠表示的数称为一个元,靠框珠表示的数称为一个元,合起来称为二元。这是珠算盘示数的基本特点,也是珠算不同笔算的一个特点,更是珠算高明之处。 二元有此消彼长的性质,有示正示负的功能,有本补之和等于10~n的规律。把二元示数的原理应用到加减运算、乘除运算、开方运算必然产生很多奇妙的算法。     

Endpoint estimates for fractional integral associated to schrödinger operators on the heisenberg groups

Let ∠= -△H~n+ V be the Schrdinger operator on the Heisenberg groups H~n,where V is a nonnegative function satisfying the reverse Hlder inequality. In this article, the author obtains the BMO_∠ and BLO_∠ estimates of the fractional integrals associated to ∠.     

BCI代数的软关联理想和软正定关联理想

给出BCI代数的软关联理想和软正定关联理想的概念,讨论软理想、软关联理想和软正定关联理想三者之间的关系,研究了两个软关联理想(软正定关联理想)的扩展交、限制交、限制并和限制差分的性质。     

轻矩阵及其推广

在R.E.Hartwig工作的基础上进一步研究了轻矩阵,得到了轻矩阵的一些特性,且把轻矩阵推广到了广义轻矩阵,得到了广义轻矩阵的一个充要条件;部分回答了文[1]中R.E.Harwtig提出的一个公开问题：当A与B都为n除非负矩阵时,刻划方程AX=XB的非负解。     

带干扰的复合负二项过程下的双险种负风险模型

本文研究了带干扰的索赔过程为复合负二项过程的双险种负风险和模型.用两种不同的方法得到了该模型的最终破产概率,还得到了Lundberg不等式,推广了经典负风险模型.     

一些图的邻点可区别关联着色

在图的关联着色概念的基础上定义了图的邻点可区别关联着色及邻点可区别关联色数,研究了圈、完全二部图、Cm.Fn图的邻点可区别关联着色,并确定了它们的邻点可区别关联色数.     

关于一类具有相同非负群逆和M-P逆的非负矩阵的进一步研究

1引言设A是n阶非负方阵．设矩阵方程(1)AXA=A,(2)XAX=X,(3)(AX)~T= AX,(4)(XA)~T=XA,(5)AX=XA．A具有非负广义逆是指存在非负方阵X满足方程(1)～(4),并记为A~(?)．A具有非负群逆是指存在非负方阵X满足方程(1),(2),(5),并记为A~#．在A~(?)存在的前提下,两者相同的充分必要条件有(a)AA~(?)=A~(?)A；(b)A~(?)=p(A),其     

渐近负相关随机域强定律的收敛率

In this paper,a notion of negative side ρ-mixing (ρ--mixing) which can be regarded as asymptotic negative association is defined,and some Rosenthal type inequalities for ρ--mixing random fields are established. The complete convergence and almost sure summability on the convergence rates with respect to the strong law of large numbers are also discussed for ρ--mixing random fields. The results obtained extend those for negatively associated sequences and ρ*-mixing random fields.     

A Central Limit Theorem for Random Fields of Negatively Associated Processes

A central limit theorem for negatively associated random fields is established under the fairly general conditions. We use the finite second moment condition instead of the finite (2+)th moment condition used by Roussas.⁽¹⁵⁾ A similar result is also given for positively associated sequences.     

关于非强平稳NA列的重对数律及其应用

本文讨论了非强平稳ＮＡ（ＮｅｙａｔｉｖｅｌｙＡｓｓｏｃｉａｔｅｄ）列的若干重对数律,并用以估计线性模型中ＮＡ误差的方差估计的一类强收敛速度．     

Weighted enumeration of spanning subgraphs in locally tree‐like graphs

Using the theory of negative association for measures and the notion of unimodularity for random weak limits of sparse graphs, we establish the validity of the cavity method for counting spanning subgraphs subject to local constraints in asymptotically tree‐like graphs. Specifically, the normalized logarithm of the associated partition function (free energy) is shown to converge along any sequence of graphs whose random weak limit is a tree, and the limit is directly expressed in terms of the unique solution to a limiting cavity equation. On a Galton–Watson tree, the latter simplifies into a recursive distributional equation which can be solved explicitly. As an illustration, we provide a new asymptotic formula for the maximum size of a b‐matching in the Erd?s–Rényi random graph with fixed average degree and diverging size, for any $b\in\mathbb{N}Using the theory of negative association for measures and the notion of unimodularity for random weak limits of sparse graphs, we establish the validity of the cavity method for counting spanning subgraphs subject to local constraints in asymptotically tree‐like graphs. Specifically, the normalized logarithm of the associated partition function (free energy) is shown to converge along any sequence of graphs whose random weak limit is a tree, and the limit is directly expressed in terms of the unique solution to a limiting cavity equation. On a Galton–Watson tree, the latter simplifies into a recursive distributional equation which can be solved explicitly. As an illustration, we provide a new asymptotic formula for the maximum size of a b‐matching in the Erd?s–Rényi random graph with fixed average degree and diverging size, for any $b\in\mathbb{N}$. To the best of our knowledge, this is the first time that correlation inequalities and unimodularity are combined together to yield a general proof of uniqueness of Gibbs measures on infinite trees. We believe that a similar argument is applicable to other Gibbs measures than those over spanning subgraphs considered here. © 2012 Wiley Periodicals, Inc. Random Struct. Alg., 2013     

Conditional negative association for competing urns

We prove conditional negative association for random variables x _j = 1 (j∈[n]:= {1…n}) , where σ(1)…σ(m) are i.i.d. from [n]. (The σ(i) 's are thought of as the locations of balls dropped independently into urns 1…n according to some common distribution, so that, for some threshold t_j, x _j is the indicator of the event that at least t_j balls land in urn j.) We mostly deal with the more general situation in which the σ(i) 's need not be identically distributed, proving results which imply conditional negative association in the i.i.d. case. Some of the results—particularly Lemma 8 on graph orientations—are thought to be of independent interest. We also give a counterexample to a negative correlation conjecture of D. Welsh, a strong version of a (still open) conjecture of G. Farr. © 2012 Wiley Periodicals, Inc. Random Struct. Alg., 2012     

Conditional limit theorems for conditionally negatively associated random variables

From the ordinary notion of negative association for a sequence of random variables, a new concept called conditional negative association is introduced. The relation between negative association and conditional negative association is answered, that is, the negative association does not imply the conditional negative association, and vice versa. The basic properties of conditional negative association are developed, which extend the corresponding ones under the non-conditioning setup. By means of these properties, some Rosenthal type inequalities for maximum partial sums of such sequences of random variables are derived, which extend the corresponding results for negatively associated random variables. As applications of these inequalities, some conditional mean convergence theorems, conditionally complete convergence results and a conditional central limit theorem stated in terms of conditional characteristic functions are established. In addition, some lemmas in the context are of independent interest.     

Empirical Euclidean likelihood for general estimating equations under association dependence

Empirical Euclidean likelihood for general estimating equations for association dependent processes is investigated. The strong consistency and asymptotic normality of the blockwise maximum empirical Euclidean likelihood estimator are presented. We show that it is more efficient than estimator without blocking. The blockwise empirical Euclidean log-likelihood ratio asymptotically follows a chi-square distribution.     

Central Limit Theorems for Asymptotically Negatively Associated Random Fields

Abstract The aim of this paper is to investigate the central limit theorems for asymptotically negatively dependent random fields under lower moment conditions or the Lindeberg condition. Results obtained improve a central limit theorem of Roussas [11] for negatively assiated fields and the main results of Su and Chi [18], and also include a central limit of theorem for weakly negatively associated random variables similar to that of Burton et al. [20]. Research supported by National Natural Science Foundation of China (No. 19701011)     

Negative Latin square type partial difference sets and amorphic association schemes with Galois rings

A partial difference set (PDS) having parameters (n², r(n?1), n+r²?3r, r²?r) is called a Latin square type PDS, while a PDS having parameters (n², r(n+1), ?n+r²+3r, r² +r) is called a negative Latin square type PDS. There are relatively few known constructions of negative Latin square type PDSs, and nearly all of these are in elementary abelian groups. We show that there are three different groups of order 256 that have all possible negative Latin square type parameters. We then give generalized constructions of negative Latin square type PDSs in 2‐groups. We conclude by discussing how these results fit into the context of amorphic association schemes and by stating some open problems. © 2009 Wiley Periodicals, Inc. J Combin Designs 17: 266‐282, 2009     

Kaplan–Meier Estimator under Association

Consider a long term study, where a series of possibly censored failure times is observed. Suppose the failure times have a common marginal distribution functionF, but they exhibit a mode of dependence characterized by positive or negative association. Under suitable regularity conditions, it is shown that the Kaplan–Meier estimatorF_nofFis uniformly strongly consistent; rates for the convergence are also provided. Similar results are established for the empirical cumulative hazard rate function involved. Furthermore, a stochastic process generated byF_nis shown to be weakly convergent to an appropriate Gaussian process. Finally, an estimator of the limiting variance of the Kaplan–Meier estimator is proposed and it is shown to be weakly convergent.