Renewed Looks at the Distribution of a Sum of Independent or Dependent Discrete Random Variables and Related Problems

Methodology and Computing in Applied Probability - Butler and Stephens (2017) have investigated the exact and approximate distributions of a sum S of independent binomial random variables with...     

Transformations Between Sturm-Liouville Problems with Eigenvalue Dependent and Independent Boundary Conditions

Explicit relationships are given connecting ‘almost’isospectral Sturm-Liouville problems with eigen-value dependent,and independent, boundary conditions, respectively. Applicationis made to various direct and inverse spectral questions. 2000Mathematics Subject Classification 34B24, 34L05, 47E05.     

Stochastic Precedence and Minima Among Dependent Variables

Methodology and Computing in Applied Probability - The notion of stochastic precedence between two random variables emerges as a relevant concept in several fields of applied probability. When one...     

Independent Random Variables in Lorentz Spaces

We investigate random variables in Lorentz spaces L_p,q. Conditionson the characteristic function are obtained which imply thata random variable belongs to the Lorentz space. Using them,we prove some estimates for the L_p,q-norm of sums of independentrandom variables. Some of these estimates are new for the spacesL_p.     

相依型不确定变量偏差和的性质

研究实值扩展负相依(END)不确定变量中部分偏差和的同题.在不确定变量期望定义和性质的基础上,利用变量之间实值负相依性和不确定性变量的性质,得到了不确定变量偏差和的上确界性质,并将其应用于风险理论,得到了较好的结果.     

相依序列加权和的收敛性

本文在相依序列下考虑加权和的ａ．ｓ．收敛性和完全收敛性．所得结论推广并改进了［１］、［２］中有关结论．     

Threshold Results for U-Statistics of Dependent Binary Variables

Large sample results for certain U-statistics, and related statistics, of binary dependent random variables are studied. The class of U-statistics include partial sums and polynomials of partial sums of a sequence of random variables. A very wide range of limit results are found. The form of the limit result can depend substantially on the magnitude of the appropriate normalizing sequence for the sum. Unexpectedly, the nature of the limit result also depends significantly on whether the degree of the U-statistic is even or odd. It is shown that dependence is a major factor contributing to this result. The limit results are illustrated with reference to a simple dynamic sequence of binary variables and a reinforced random walk.     

A Remark on Self-Normalization for Dependent Random Variables

Let (X _t , t ∈ Z) be a stationary process, and let S _n = ∑_{1⩽ i⩽n} X _i . In this paper, we consider the central limit theorem for the self-normalized sequence S _n /U _n , where U _n ² = ∑_1⩽j⩽N Y _j ² , Y _j = ∑_{(j−1)m<i⩽jm} X _i , n = mN. We show how such a self-normalization works for AR(1) and MA(q) processes.__________Published in Lietuvos Matematikos Rinkinys, Vol. 45, No. 2, pp. 173–183, April–June, 2005.     

随机变量独立性与不相关的一点教学思考

通过几个教学案例,分析了随机变量的独立性的重要性及它与不相关的关系,阐述了在概率论与数理统计课程教学中如何培养学生的数学思维创新能力.     

两两独立序列加权和的L~r收敛性

讨论了两两独立随机变量列加权和在满足r(1≤r<2)阶Ces`aro一致可积条件下的Lr收敛性,获得了与独立情形一致的结果.用相似的方法,对于其它相依或混合序列(如两两NQD列,φ-混合序列,ρ-混合序列)也有相同的结果.     

两个变量的Hardy型积分不等式

建立了两个独立变量函数的新的Hardy型积分不等式.     

独立粗糙变量序列的强收敛性

在信赖性理论的公理化基础上,利用截尾方法,得到独立粗糙变量序列的不等式、Borel-Cantalli引理及三级数定理,推广了某些已有的结果。     

On the Convergence of Series of Dependent Random Variables

Journal of Theoretical Probability - Given a sequence $$(X_n)$$ of symmetrical random variables taking values in a Hilbert space, an interesting open problem is to determine the conditions under...     

Almost-Sure Results for a Class of Dependent Random Variables

The aim of this note is to establish almost-sure Marcinkiewicz-Zygmund type results for a class of random variables indexed by _d ⁺ —the positive d-dimensional lattice points—and having maximal coefficient of correlation strictly smaller than 1. The class of applications include filters of certain Gaussian sequences and Markov processes.     

Strong Laws for Martingale Differences and Independent Random Variables

A strong law of large numbers (SLLN) for martingale differences {X _n,_n,n1} permitting constant, random or hybrid normalizations, is obtained via a related SLLN for their conditional variances E{X _n ² |_n-1}n1. This, in turn, leads to martingale generalizations of known results for sums of independent random variables. Moreover, in the independent case, simple conditions are given for a generalized SLLN which contains the classical result of Kolmogorov when the variables are i.i.d.     

Some Exponential Inequalities for Negatively Orthant Dependent Random Variables

Acta Mathematicae Applicatae Sinica, English Series - In the paper, we establish some exponential inequalities for non-identically distributed negatively orthant dependent (NOD, for short) random...