关于重尾分布间的控制关系及其应用

得到了能控制一切轻尾分布及一切轻度重尾分布的分布的等价条件,得到了能控制一切轻尾分布的分布的等价条件,讨论了分布与其相应的均衡分布之间的控制关系,并给出了上述控制关系在和的分布的封闭性等方面的应用.     

若干矩阵Γ分布的相关分布

本文研究了与矩阵Γ分布相关的若干分布的密度函数,利用矩阵Γ分布的特征函数和它的Bartlett分解等方法,获得了与矩阵Γ分布相关的几个分布的密度函数解析表达式,它们包括Γ分布随机矩阵的子矩阵、行列式、迹和特征根的分布密度,进一步还得到了相关系数矩阵的分布密度函数形式.     

若干矩阵Г分布的相关分布

本文研究了与矩阵Г分布相关的若干分布的密度函数，利用矩阵Г分布的特征函数和它的Bartlett分解等方法，获得了与矩阵Г分布相关的几个分布的密度函数解析表达式，它们包括Г分布随机矩阵的子矩阵、行列式、迹和特征根的分布密度，进一步还得到了相关系数矩阵的分布密度函数形式．     

以截尾伽玛分布为先验分布的产品失效率的贝叶斯估计

本文研究了基于泊松分布的产品失效率估计问题.利用贝叶斯统计推断方法,获得了以截尾伽玛分布为先验分布时,产品失效率的贝叶斯估计和相关性质,推广了以伽玛分布为先验分布的贝叶斯估计结果.     

Marshall-Olkin扩展重尾分布的刻画

利用Marshall-Olkin提出构造分布的方法,以重尾分布F作为基础,提出了Marshall-Olkin扩展重尾分布G,根据常见重尾分布子族的定义及其等价关系,分析了F与G的相关性质,对于重尾分布族,G具有封闭性,尾等价性,同时在连续型分布情形下,讨论了F与G的密度函数之间及风险率函数之间的关系.最后,将Marshall-Olkin扩展重尾分布应用于实际数据中,并在拟合数据方面与原分布进行比较,表明扩展分布要优于原分布.     

风险非同质时索赔次数的分布拟合的估计与检验问题

在非寿险精算中 ,索赔次数的分布一般假设为泊松分布 P(λ) .风险非同质时 λ的分布称为混合分布 .本文考虑了混合分布为三参数伽玛分布时的参数估计以及位置参数的检验问题     

基于优势关系下不协调目标信息系统的分布约简

在基于优势关系下的不协调目标信息系统中引入了分布约简和最大分布约简的概念,并讨论了二者之间的关系,而且得到了分布和最大分布约简的判定定理以及辨识矩阵,建立了不协调目标信息系统的分布和最大分布约简的具体方法,同时通过实例验证了该方法的有效性,从而进一步丰富了粗糙集理论。     

尾年金分布的存在性和结构

本文主要是在年金分布的基础上, 推广、定义并研究了一类$r$尾年金分布的存在性和结构, 给出了这类分布的存在性条件, 证明了在一定条件下, $r$尾年金分布是年金分布与某一特殊$r$尾年金分布的混合.     

超几何分布的数字特征和概率计算的探讨

用定义法、性质法、概率母函数法三种方法探索了超几何分布的数学期望和方差的求法,同时又给出了超几何分布、二项分布、泊松分布和正态分布之间的近似关系,从而解决了超几何分布的概率计算问题.     

极值分布的一个注记

本文对PH极值分布进行了推广,应用构造相关联的Markov过程的方法,证明了n个相互独立的PH随机变量构成的次序随机变量的分布仍是PH分布。并给出了次序PH随机变量分布表达式的表示方法,本文同时也给出了次序PH随机变量的联合生存分布,本文最后给出了次序PH随机变量在可靠性理论与更新理论中的应用。     

Outlier Eigenvalues for Deformed I.I.D. Random Matrices

We consider a square random matrix of size N of the form A + Y where A is deterministic and Y has i.i.d. entries with variance 1/N. Under mild assumptions, as N grows the empirical distribution of the eigenvalues of A + Y converges weakly to a limit probability measure β on the complex plane. This work is devoted to the study of the outlier eigenvalues, i.e., eigenvalues in the complement of the support of β. Even in the simplest cases, a variety of interesting phenomena can occur. As in earlier works, we give a sufficient condition to guarantee that outliers are stable and provide examples where their fluctuations vary with the particular distribution of the entries of Y or the Jordan decomposition of A. We also exhibit concrete examples where the outlier eigenvalues converge in distribution to the zeros of a Gaussian analytic function. © 2016 Wiley Periodicals, Inc.     

QNQL过程在排队论中的应用（Ⅰ）：输入过程（独立同分布情形）

本文在“相邻两个顾客到达时间间隔独立同分布”这个假定下，讨论输入过程Ｎ（ｔ）的拉氏变换及概率分布问题．     

Convergence in Distribution of Products of I.I.D. Nonnegative Matrices

Let (X _i) be a sequence of m × m i.i.d. stochastic matrices with distribution . Then ⁿ is the distribution of X _n X _n–1 ...X ₁. Simple sufficient conditions for the weak convergence of ( ⁿ ) are presented here. An extremely simple (and verifiable) necessary and sufficient condition is provided for m= 3. The method for m= 3 works for m> 3 even though calculations are more involved for higher values of m. We also discuss the purity of the limit distribution for m2.     

A local invariance principle. I

Let be a sequence of independent, identically distributed random variables,. We set and let be the distribution in of the corresponding random polygonal line with vertices at the points, while is the distribution of a standard process of Brownian motion. In the paper one proves that under certain additional conditions imposed on the distribution of the variables for any functional from a very large class, the distributions of the random: variables converge in variation to the distribution of the variable.Translated from Zapiski Nauchnykh Seminarov Leningradskogo Otdeleniya Matematicheskogo Instituta im. V. A. Steklova AN SSSR, Vol. 97, pp. 45–50, 1980.     

Expansions for the Distributions of Some Normalized Summations of Random Numbers of I.I.D. Random Variables

The central limit theorem for a normalized summation of random number of i.i.d. random variables is well known. In this paper we improve the central limit theorem by providing a two-term expansion for the distribution when the random number is the first time that a simple random walk exceeds a given level. Some numerical evidences are provided to show that this expansion is more accurate than the simple normality approximation for a specific problem considered.     

Characterizations of multivariate normality. I. Through independence of some statistics

It is established that a vector variable (X₁, …, X_k) has a multivariate normal distribution if for each X_i the regression on the rest is linear and the conditional distribution about the regression does not depend on the rest of the variables, provided the regression coefficients satisfy some mild conditions. The result is extended to the case where X_i themselves are vector variables.     

Estimating means from a non-I.I.D. Mixture of Poisson samples

In this paper, a family of estimators for estimating means when mixing two independent Poisson samples is proposed. This family is based on the probability-generating function of the Poisson distribution and is offered as an alternative to the maximum likelihood estimators, which have some drawbacks. These estimators include the method of moments estimators as a special limiting case.     

Random complex zeroes,I. Asymptotic normality

We consider three models (elliptic, flat and hyperbolic) of Gaussian random analytic functions distinguished by invariance of their zeroes distribution. Asymptotic normality is proven for smooth functionals (linear statistics) of the set of zeroes. Supported by the Israel Science Foundation of the Israel Academy of Sciences and Humanities.     

Random “granular” images. I

One investigates statistical properties of various geometric characteritics of random images, typical for photography, photodiode matrices, etc. One discusses the Poisson model of the image, one gives a characterization of the functionals defining the coordinates of point images, one computes the distribution density of the coordinates.Translated from Zapiski Nauchnykh Seminarov Leningradskogo Otdeleniya Matematicheskogo Instituta im. V. A. Steklova AN SSSR, Vol. 153, pp. 73–96, 1986.     

Complete Theories with Finitely Many Countable Models. I

A syntactic characterization is furnished for the class of elementary complete theories with finitely many countable models, which is the analog of a known theorem by Ryll-Nardzewski on countably categorical theories, and is based on classifying the theories by Rudin-Keisler quasiorders and distribution functions of a number of models limit over types.