关于负超几何分布期望与方差算法的注记

研究了非还原取样模型中负超几何随机变量的联合分布,得到了若干有用的推论.据此给出了负超几何分布的期望和方差的一种分解算法.     

计算超几何分布的数学期望与方差的一种简便方法

超几何分布的数学期望和方差，如果按照定义直接计算比较麻烦，本文利用一种摸球模型的结果以及数学期望和方差的性质，给出了求超几何分布的数学期望和方差的一种简便方法，同时用该方法证明了常用的一个组合计算公式。     

超几何分布的数学期望和方差的定义求法

利用排列的性质,从超几何分布的定义出发,针对服从超几何分布的随机变量,给出直接计算其数学期望和方差的一种方法．     

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.     

不同模型下ES风险度量的计算

给出当金融资产遵从几何布朗运动时期望损失的计算。当金融资产价格的对数收益率服从均值方程为ARMA模型,方差方程为GARCH(s,n)模型,而均值修正后的收益率分别服从正态分布、t分布和GED分布时,给出了期望损失的计算。     

离散型随机变量高阶原点矩的一种新的递推计算方法

针对服从二项、泊松、几何、负二项、超几何、负超几何以及对数级数分布等离散型随机变量,给出了求其高阶原点矩的一个较为简单的递推计算方法.不仅非常容易地求出这些离散型随机变量的高阶原点矩,避免了计算阶乘矩或求导等复杂的运算,而且便于学生理解.论文还给出了这些离散型随机变量的3阶和4阶原点矩的表达式.     

负二项分布随机变量数字特征的求解

本文给出了生产实践中被广泛应用的负二项分布的五种定义,研究了该分布对应随机变量的期望、方差等数字特征的求解,汇总了负二项分布与其它分布之间的关系.     

离散型指数差分布

本文提出了一个离散型概率分布:指数差分布,推导了该分布的最可能成功次数、数学期望和方差,探讨了该分布与几何分布的关系,给出了该分布在马尔可夫链模型中的应用。     

多项几何分布（英文）

本文研究了在伯努利试验下的收集问题,利用混料格子点集的理论,推导出了多项几何分布的概率函数.在伯努利试验中,如果假设各种试验结果发生的概率都相等,进一步提出了均匀多项几何分布.我们得到了两类分布的概率函数以及期望与方差,通过模拟验证了这两类分布与正态分布的差异,并由模拟结果建立关于概率与试验次数的多项式回归模型,使用该模型可以有效的简化计算.     

i．i．d随机变量随机和的数字特征

讨论了i．i．d的随机变量随机和的数学期望和方差、特征函数以及矩母函数的计算公式。并对求和个数服从几何分布和Possion分布，随机变量服从指数分布时给出了直接结果．     

Approximation of inverse moments of discrete distributions

For a wide class of discrete distributions, we derive a representation of the inverse (negative) moments through the Stirling numbers of the first kind and inverse factorial moments. We specialize the results for the Poisson, binomial, hypergeometric and negative binomial distributions.     

ON THE EXPECTATION AND VARIANCE OF HAMMING DISTANCE BETWEEN TWO I.I.D RANDOM VECTORS

1.IntroductionLetFZn={0,1}"beann-dimensionalvectorspaceoverthebinaryfieldFZ={0,1}.TheHammingdistancebetweentwovectorsx=(xl,'tx.)andy=(yi,'ty.)isthenumberofcoordinateswheretheydiffer,andisdenotedbydH(x,y),dH(X,y)=ZIXi~ail.i=1TheHammingweightofxisthenumberofnon-zerocoordinates,andisdenotedbyWH(x).ObviouslyAH(x)=dH(x,0),where0isthezerovector.Thescalarproductofxandyis(x,y)=xlyl ' xestinF2.ForasetAgFZn,IAIdenotesthecardinalityofA.TheaveragedistanceinAisdefinedby*Thisresearchissupp…     

A Weighted Likelihood Ratio of Two Related Negative Hypergeomeric Distributions

In this paper we consider some related negative hypergeometric distributions arising from the problem of sampling without replacement from an urn containing balls of different colours and in different proportions but stopping only after some specific number of balls of different colours have been obtained. With the aid of some simple recurrence relations and identities we obtain in the case of two colours the moments for the maximum negative hypergeometric distribution, the minimum negative hypergeometric distribution,the likelihood ratio negative hypergeometric distribution and consequently the likelihood proportional negative hypergeometric distributiuon. To the extent that the sampling scheme is applicable to modelling data as illustrated with a biological example and in fact many situations of estimating Bernoulli parameters for binary traits within a finite population, these are important first-step results.     

Moments of Ramanujan?s generalized elliptic integrals and extensions of Catalan?s constant

We undertake a thorough investigation of the moments of Ramanujan?s alternative elliptic integrals and of related hypergeometric functions. Along the way we are able to give some surprising closed forms for Catalan-related constants and various new hypergeometric identities.     

Summations of linear recurrent sequences

We give an extension of Sister Celine’s method of proving hypergeometric sum identities that allows it to handle a larger variety of input summands. In particular, we extend the summand to powers of a C-finite sequence times a hypergeometric term. We then apply this to several problems. Some of these applications give new results, and some reprove already known results in an automated way.     

模糊随机变量及其概率分布

本文在模糊σ－代数及模糊数的极大全序子集之上定义了模糊随机变量，进而首次定义了客观实用的模糊随机变量的概率分布函数，并讨论了数学期望及方差等数字特征。     

Certain estimation problems for multivariate hypergeometric models

Certain estimation problems associated with the multivariate hypergeometric models: the property of completeness, maximum likelihood estimates of the parameters of multivariate negative hypergeometric, multivariate negative inverse hypergeometric, Bayesian estimation of the parameters of multivariate hypergeometric and multivariate inverse hypergeometrics are discussed in this paper. A two stage approach for generating the prior distribution, first by setting up a parametric super population and then choosing a prior distribution is followed. Posterior expectations and variances of certain functions of the parameters of the finite population are provided in cases of direct and inverse sampling procedures. It is shown that under extreme diffuseness of prior knowledge the posterior distribution of the finite population mean has an approximate mean and variance (N-n)S ²/Nn, providing a Bayesian interpretation for the classical unbiased estimates in traditional sample survey theory.