The convergence on spectrum of sample covariance matrices for information-plus-noise type data

In this paper,we consider the limiting spectral distribution of the information-plusnoise type sample covariance matrices Cn =1/N (Rn + σXn) (Rn + σXn)*,under the assumption that the entries of Xn are ...     

随机变量变换分布的若干推论及应用

给出了随机变量变换分布的三个推论，这些推论提供了在不同变换下求二维随机变量的函数的概率密度的计算公式，实例应用表明，这些公式应用简便，灵活，实用．     

随机变量数学期望的一个注记

介绍一种计算随机变量数学期望的方法,利用这种方法容易得到数学期望的相关性质,很多概率与矩的不等式证明也因之变得更为简洁.     

二维连续型随机变量函数分布的一个定理

给出求二维连续型随机变量函数分布的一个定理,并籍以导出二维随机变量和差积商的概率密度函数公式.     

Three-stage Stiffly Accurate Runge-Kutta Methods for Stiff Stochastic Differential Equations

In this paper we discuss diagonally implicit and semi-implicit methods based on the three-stage stiffly accurate Runge-Kutta methods for solving Stratonovich stochastic differential equations（SDEs）.Two methods,a three-stage stiffly accurate semi-implicit（SASI3） method and a three-stage stiffly accurate diagonally implicit （SADI3） method,are constructed in this paper.In particular,the truncated random variable is used in the implicit method.The stability properties and numerical results show the effectiveness of these methods in the pathwise approximation of stiff SDEs.     

NOD随机变量阵列加权乘积和的完全收敛性

利用NOD随机变量的性质,研究了行为NOD随机变量阵列加权乘积和的完全收敛性,获得了一些新的结果,所得的结果推广和改进了已知的一些文献中的一系列结果.     

α混合随机变量序列部分和乘积的几乎处处中心极限定理

利用子序列等方法,获得α混合随机变量序列部分和乘积的几乎处处中心极限定理的更优结果,改进了相关文献的结果.     

LARGE DEVIATIONS AND MODERATE DEVIATIONS FOR SUMS OF NEGATIVELY DEPENDENT RANDOM VARIABLES

In this article, we obtain the large deviations and moderate deviations for negatively dependent (ND) and non-identically distributed random variables defined on (-∞, +∞). The results show that for some non-identical random variables, precise large deviations and moderate deviations remain insensitive to negative dependence structure.     

迷雾散尽 本质凸显——由一个数学期望问题引发的思考与探究

在一次巡视学生独立作业的过程中,发现一个看似简单的问题,好多人没有做(空着),做的人中,答案正确的也是寥寥无几.为了寻找学生思路受阻和解答错误的原因,笔者记下题目开始思考.题目是     

Asymptotic tail probability of randomly weighted sums of dependent random variables with dominated variation

This paper investigates the asymptotic behavior of tail probability of randomly weighted sums of dependent and real-valued random variables with dominated variation, where the weights form another sequence of nonnegative random variables. The result we obtain extends the corresponding result of Wang and Tang[7].