Γ-分布类的条件概率封闭性

X服从参数α和λ的Γ-分布,V与Y分别服从参数θ和λ的指数分布.我们证明了:在X＜Y的条件下,X的条件分布是参数α和θ+λ的Γ-分布;在X＜V＜X+Y的条件下,V的条件分布是参数α+1和θ+λ的Γ-分布.称此类性质为Γ-分布类的条件概率封闭性.对离散的负二项分布也证明了类似的结果.     

Г-分布类的条件概率封闭性

X服从参数α和λ的Γ 分布,V与Y分别服从参数θ和λ的指数分布。我们证明了:在X相似文献   

条件Erlang分布双参数加法定理的推广

X(m)和Y(k)服从参数(m,λ)和(k,μ)的Erlang分布且相互独立.证明了在X(m)相似文献   

条件Erlang分布的双参数加法定理

X(γ)和Y(k)服从参数(γ,λ)和(k,μ)的Erlang分布且相互独立.本文证明了在X(γ)相似文献   

一类双分数布朗运动迭代过程局部时的存在性和联合连续性

本文研究取值在Rd上的一类双分数布朗运动迭代过程X(t)=(X1(t),…,Xd(t))局部时的存在性和联合连续性.这类过程是由阶为α的严格稳定的Lévy过程{Y(t),t0}替代双分数布朗运动{BH,K(t),t0}中的时间参数t所构成的双分数布朗运动迭代过程{Z(t)=BH,K(Y(t)),t0},其中0α≤2,0H1,0K≤1,且BH,K与Y是相互独立的,并且X1,…,Xd是相互独立的,且与Z同分布.     

不独立和不相关

若随机变量 X 和 Y 的相关系数 r(X,Y)=0,称 X 与 Y 不相关,众所周知,独立变量一定不相关(自然要求方差有限),不独立变量也可以不相关,单位圆内的均匀分布即其一例,这种例子可随意举出很多,这启发我们提出下面的问题任意给定两个一维分布 F 和 G,其方差都非零有限.是否存在两个随机变量 X,Y ,使得:1)X 有分布 F,Y 有分布 G.2)X,Y 不独立.3)r(X,Y)=0.我们的直觉是这问题有肯定的回答,但证明并非一目了然,诚然,这不是什么很重要或很     

非对称损失函数下Burr Ⅻ型分布可靠性指标的Bayes估计

本文研究了R=P(Y＜X)在两种非对称损失函数下的Bayes估计问题,其中随机变量X和Y相互独立且服从不同的Burr XII型分布.利用Lindley近似方法,获得了Bayes估计的显式近似表达式,通过随机模拟比较了不同损失函数下的Bayes估计的性质.     

问题５与问题６

正问题5(供题者:复旦大学应坚刚)向平面随机地投掷一根长为2的针.求(i)针仅与平行线■之一相交的概率;(ii)针与平行线■相交的概率.问题6(供题者:浙江大学张立新)设X和Y是相互独立的非退化随机变量,a为实数.假设X+Y与aX同分布.证明     

二元Cuadra-Auge型帕累托分布的相关性及渐近独立性

二元Cuadra-Auge型帕累托分布是一个二元对称分布,在本文中,分别讨论了二元Cuadra-Auge型帕累托分布的性质与相关性及渐近独立性,导出了二元Cuadra-Auge型帕累托分布的若干性质;证明了X,Y之间的相关系数介于零与四分之三之间,且X,Y之间渐近独立.     

老出版社奖金核定数学模型

针对老出版社普遍存在的奖金核定难问题,创建了一个数学模型:对经营部门,Y=X1+X2;对职能部门,Y=αY1;介绍了各参数的确定方法,并以实例形式作了说明.本模型具有协调稳定与发展、发扬民主、可操作性强、相对公平等优点.     

方差分量线性模型中回归系数和参数的所有可容许线性估计

对固定效应方差分量模型，在矩阵损失（ｄ－Ｓ＿τ）（ｄ－Ｓ＿τ）＇下，我们给出了线性可估函数Ｓτ的线性估计在一切估计类中可容许的充要条件；对具有两个方差分量的随机效应线性模型在矩阵损失（ｄ－Ｓα－Ｑβ）（ｄ－Ｓα－Ｑβ）＇下，我们给出了线性可估函数Ｓα＋Ｑβ的线性估计在一切估计类中可容许的充要条件。     

一类两个随机变量函数的分布

给出了随机变量X,y分别是离散、连续不同类型时,其函数Z=g（X,y）分布的一般求解方法和应用举例．     

SOME POSTERIOR DISTRIBUTIONS FOR THE LAPLACE MEAN

Two posterior distributions for the mean of the Laplace distribution are obtained by deriving the distributions of the product XY and the ratio X/Y when X and Y are Student＇s t and Laplace random variables distributed independently of each other. Tabulations of the associated percentage points are given along with computer programs for generating them.     

Local Solvability for a Class of Nonhomogeneous Left Invariant Differential Operators on HR \bigotimes Rk

In this paper we discuss tbe local solvability of the following nonhomogeneous left invariant differential operators on the nilpotent Lie group H_n⊗R^K: P(X, Y, T, Z) = Σ_{|α+β|+ζ+|y|≤m|α+β|+2l=a}a_{αβly}X^αY^βT^lZ^y where X_j, Y_j (j = 1, 2, …, n), T, Z_j(j = l, 2, …, K) are bases of left invariant vector fields on H_n⊗R^K and a_{αβly} are complex constants.     

矩阵损失下随机回归系数和参数的线性Minimax估计

对于一般的随机效应线性模型Y=Xβ+ε,这里β和ε分别是p维和n维的随机向量,且E(βε)=(Aa0),Cov(βε)=σ2(V10 0V2),(Vi≥0,i=1,2)我们定义了Sα+Qβ的线性Minimax估计,在一定条件下得到了Sα+Qβ在线性估计类中的Minimax估计,并在几乎处处意义下证明了它的唯一性.     

LARGE DEVIATION FOR THE EMPIRICAL CORRELATION COEFFICIENT OF TWO GAUSSIAN RANDOM VARIABLES

In this article,the author obtains the large deviation principles for the empir- ical correlation coefficient of two Gaussian random variables X and Y.Especially,when considering two independent Gaussian random variables X,Y with the means EX. EY (both known),wherein the author gives two kinds of different proofs and gets the same results.     

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本文研究了独立随机变量之和的绝对矩的几个性质, 其中包括$\ep|X+Y|-\ep|X-Y|$的表达式, 这里$X$和$Y$是相互独立的随机变量.     

A consistent local linear estimator of the covariate adjusted correlation coefficient

Consider the correlation between two random variables (X, Y), both not directly observed. One only observes X? = φ(1)(U)X + φ(2)(U) and ? = ψ(1)(U)Y + ψ(2)(U), where all four functions {φ(l)(·),ψ(l)(·), l = 1, 2} are unknown/unspecified smooth functions of an observable covariate U. We consider consistent estimation of the correlation between the unobserved variables X and Y, adjusted for the above general dual additive and multiplicative effects of U, based on the observed data (X?, ?, U).     

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.     

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??This paper deals with reliability inference results in $R=\pr(Y相似文献