Positive dependence orderings

Summary This paper presents a systematic basis for studying orderings of bivariate distributions according to their degree of positive dependence. The general concept of a positive dependence ordering (PDO) is introduced and its properties discussed. Based on this concept, a new ordering of bivariate distributions according to their degree of total positivity of order two (TP₂) is presented, and is shown to be a PDO. Properties of this TP₂ ordering are derived and numerous applications are presented. The work of this author is supported by the National Science Foundation under Grant MCS-8301361. The work of this author is sponsored by the Air Force Office of Scientific Research, Air Force Systems Command under Contract F49629-82-K-001. Reproduction in whole of in part is permitted for any purpose of the United States Government.     

A concept of negative dependence using stochastic ordering

A concept of negative dependence called negative dependence by stochastic ordering is introduced. This concept satisfies various closure properties. It is shown that three models for negetive dependence satisfy it and that it implies the basic negative orthant inequalities. This concept is also satisfied by the multinomial, multivariate hypergeometric. Dirichlet and Dirichlet compound multinomial distributions. Furthermore, the joint distribution of ranks of a sample and the multivariate normal with nonpositive pairwise correlations also satisfy this condition. The positive dependence analog of this condition is also studied.     

The law of the iterated logarithm for positively dependent random variables

The Levy's type maximal inequality is a key to establish the law of the iterated logarithm for associated random variables. Unfortunately, this type inequality cannot be obtained for a generalization of association, i.e., linear positive quadrant dependence, because of their special dependence structure. The purpose of this paper is to provide a different approach to obtain a law of the iterated logarithm for a sequence of linear positive quadrant dependent random variables.     

Weak association of random variables

The dependence concept of weak association is introduced and is shown to be equivalent to positive quadrant dependence. Furthermore, a characterization of independence in the class of positive quadrant dependent random variables by means of moment conditions is proved. Both results generalize some theorems proved by Lehmann and Jogdeo for the two- and three-dimensional case.     

A general theory of some positive dependence notions

A general theory of concepts of positive dependence, which are weaker than association but stronger than orthant dependence, is developed. A random vector X is associated if and only if $\text{P(}\text{X}\text{∈ A ? B) ≥ P(}\text{X}\text{∈ A) P(}\text{X}\text{∈ B)}$ for all open upper sets A and B. By requiring the above inequality to hold only for some open upper sets A and B various notions of positive dependence which are weaker than association are obtained. First a general theory is given and then the results are specialized to some concepts of a particular interest. Various properties and interrelationships are derived and some applications are discussed.     

基于Copula理论的随机变量的相关性

研究了用Copula表示的相关性度量σ相比于Pearsen线性相关系数r和和谐性度量τ与ρ的优良性质,求解了4个最大不可交换Copula的相关性度量σ.为了便于计算,引入基于L2距离的相关性度量φ,求解了某个单点值给定时Copula最优上下界的相关性度量φU和φL,作为特例,得到了4个最大不可交换Copula的另一种相关性度量φ.     

Some concepts of positive dependence for bivariate interchangeable distributions

In this work we consider some familiar and some new concepts of positive dependence for interchangeable bivariate distributions. By characterizing distributions which are positively dependent according to some of these concepts, we indicate real situations in which these concepts arise naturally. For the various families of positively dependent distributions we prove some closure properties and demonstrate all the possible logical relations. Some inequalities are shown and applied to determine whether under- (or over-) estimates, of various probabilistic quantities, occur when a positively dependent distribution is assumed (falsely) to be the product of its marginals (that is, when two positively dependent random variables are assumed, falsely, to be independent). Specific applications in reliability theory, statistical mechanics and reversible Markov processes are discussed. This work was partially supported by National Science Foundation GP-30707X1. It is part of the author's Ph.D. dissertation prepared at the University of Rochester and supervised by A. W. Marshall. Now at Indiana University.     

Measures of the functional dependence of random vectors

In this work, we define a set of properties that any measure of functional dependence that exists between random vectors should possess. We also construct measures of functional dependence and show that they satisfy the properties mentioned above. Relationships between these measures and previously defined measures of functional dependence between random variables are discussed.     

含有一阶导数的四阶边值问题正解的存在性

研究了含有一阶导数的四阶边值问题,利用度理论构造出的一个新的不动点定理,由Green函数的性质,给出了一类含有导数的四阶边值问题正解存在的充分条件,得到了边值问题正解存在的一些新结果.     

Validation of association

Recognizing, quantifying and visualizing associations between two variables is increasingly important. This paper investigates how a new function-valued measure of dependence, the quantile dependence function, can be used to construct tests for independence and to provide an easily interpretable diagnostic plot of existing departures from the null model. The dependence function is designed to detect general dependence structure between variables in quantiles of the joint distribution. It gives an insight into how the dependence structure changes in different parts of the joint distribution. We define new estimators of the dependence function, discuss some of their properties, and apply them to construct new tests of independence. Numerical evidence is given to the tests benefits against three recognized independence tests introduced in the previous years. In real-data analysis, we offer the use of our tests and the graphical presentation of the underlying dependence structure.     

Two concepts of singularity for matrices over semirings

The two common concepts of singularity for matrices over semirings are being studied since the 1970’s and arise from natural generalizations of the determinant and linear dependence. They were introduced in the context of schedule algebras by Gondran and Minoux, who proved later that the concepts discussed are equivalent over any selective invertible semiring. We present an approach that uses a generalization of power series arithmetic and, in particular, allows to derive a short proof for the theorem of Gondran and Minoux. Our main result is a complete concise characterization of semirings over which the two concepts of singularity are equivalent.     

一类梁方程正解的存在性和对参数的依赖性

应用锥不动点定理并结合Banach空间中的半序结构,研究了一类梁方程的可解性问题.不仅得到了梁方程正解的存在性结果,并且讨论了梁方程正解对参数的依赖性.注意到梁方程中含有正参数λ和L~p-可积函数,获得的结果是新的,并从本质上推广了已有文献的结果.     

Multivariate Distributions from Mixtures of Max-Infinitely Divisible Distributions

A class of multivariate distributions that are mixtures of the positive powers of a max-infinitely divisible distribution are studied. A subclass has the property that all weighted minima or maxima belong to a given location or scale family. By choosing appropriate parametric families for the mixing distribution and the distribution being mixed, families of multivariate copulas with a flexible dependence structure and with closed form cumulative distribution functions are obtained. Some dependence properties of the class, as well as some characterizations, are given. Conditions for max-infinite divisibility of multivariate distributions are obtained.     

Curvatures and Currents for Unions of Sets with Positive Reach, II

A class of subsets of ^d which can berepresented as locally finite unions of sets with positive reach isconsidered. It plays a role in PDE's on manifolds with singularities.For such a set, the unit normal cycle (determining the d – 1curvature measures) is introduced as a (d – 1)-currentsupported by the unit normal bundle and its properties are established.It is shown that, under mild additional assumptions, the unit normalcycle (and, hence, also the curvature measures) of such a set can beapproximated by that of a close parallel body or, alternatively, by themirror image of that of the closure of the complement of the parallelbody (which has positive reach). Finally, the mixed curvature measuresof two sets of this class are introduced and a translative integralgeometric formula for curvature measures is proved.     

浅谈正定二次型的习题课设计

在高等代数的实二次型内容中,正定二次型占有特殊的地位.本文从概念的回顾、正定二次型与正定矩阵的判断、二次型正定及矩阵正定的性质、其它类型二次型四个方面来设计正定二次型的习题课,并通过具体例子说明例题、习题精选的原则.     

Bivariate extreme value distributions based on polynomial dependence functions

In this paper, we are concerned with bivariate differentiable models for joint extremes for dependent data sets. This question is often raised in hydrology and economics when the risk driven by two (or more) factors has to be quantified. Here we give a full characterization of polynomial models by means of their dependence function and dependence measure. Copyright © 2006 John Wiley & Sons, Ltd.     

Characterizing and Generating Bivariate Empirical Rank Distributions Satisfying Certain Positive Dependence Concepts

Abstract

This article introduces an approach for characterizing the classes of empirical distributions that satisfy certain positive dependence notions. Mathematically, this can be expressed as studying certain subsets of the class S_N of permutations of 1, …, N, where each subset corresponds to some positive dependence notions. Explicit techniques for it-eratively characterizing subsets of S_N that satisfy certain positive dependence concepts are obtained and various counting formulas are given. Based on these techniques, graph-theoretic methods are used to introduce new and more efficient algorithms for constructively generating and enumerating the elements of various of these subsets of S_N. For example, the class of positively quadrant dependent permutations in S_N is characterized in this fashion.     

基于Copula函数的股指尾部相关性研究——以道琼斯工业指数与恒生指数为例

鉴于两步参数估计法在应用中存在误差大、计算复杂等缺陷,采用基于经验分布的半参数估计与非参数估计法确定相应边缘分布与Copula参数,对突发事件下的道琼斯工业指数与恒生指数之间的尾部相关性进行量化.研究发现ClaytonCopula,Gumbel Copula能够较好地刻画股指收益率序列间的尾部相关关系;道指与恒生指数存在着正的尾部相关且这种相关是非对称性的;在各个置信水平上,下尾损失均较上尾收益高,且下尾相关系数的增长幅度远大于上尾相关系数的增长幅度;极端事件造成的道指收益的剧烈下跌引发了恒生指数收益更强烈的相关反应,其造成的影响远超过两个市场同时上涨时的作用.     

Opportunistic Maintenance for Multi-component Shock Models

This paper is concerned with opportunistic maintenance on a multi-component cumulative damage shock model with stochastically dependent components. A component fails when its cumulative damage exceeds a given threshold, and any such a failure creates a maintenance opportunity, and triggers a simultaneous repair on all the components, including the non-failed ones, such that damages accumulated at various components are reduced to certain degrees. Utilizing the coupling method, stochastic maintenance comparisons on failure occurrences under different model parameters are obtained. Some positive dependence properties of this multi-component shock model are also presented.Lirong Cui: Supported by the NSF of China grant 70371048.Haijun Li: Supported in part by the NSF grant DMI 9812994.     

Reducing model risk via positive and negative dependence assumptions

We give analytical bounds on the Value-at-Risk and on convex risk measures for a portfolio of random variables with fixed marginal distributions under an additional positive dependence structure. We show that assuming positive dependence information in our model leads to reduced dependence uncertainty spreads compared to the case where only marginals information is known. In more detail, we show that in our model the assumption of a positive dependence structure improves the best-possible lower estimate of a risk measure, while leaving unchanged its worst-possible upper risk bounds. In a similar way, we derive for convex risk measures that the assumption of a negative dependence structure leads to improved upper bounds for the risk while it does not help to increase the lower risk bounds in an essential way. As a result we find that additional assumptions on the dependence structure may result in essentially improved risk bounds.