估计真实回答的概率和敏感指标的总体均值

本文提出一种同时估计个体报告真实回答的概率T和敏感指标均值μ_x的无关问题模型,文中讨论了T和μ_x估计量的性质以及样本容量的匹配.本文计算了所提出方法与直接调查方法的相对效率,结论表明,存在不真实回答情况下,本文提出方法可以比直接调查更有效.     

对称分布下中位数排序集样本均值的有效性证明

总体均值的估计在整个抽样理论里扮演着无可争议的主角,而估计的好坏很大程度上依赖于抽样设计.文章从理论上证明了在对称分布下,基于中位数排序集抽样的样本均值作为总体均值的估计比简单随机抽样下样本均值作为总体均值的估计更有效.小样本情形下的两个数值例子和一个实例进一步验证了这个理论结果.     

当方差未知时选取有最大均值总体的两阶段抽样方案

考虑ｋ个有连续分布Ｆｉ＝Ｆ（ｘ－μｉ／σ）的总体，ｉ＝１，．．．，ｋ。其中μｉ和σ均未知，我们通过两阶段抽取样本以得到最大均值的那个总体，第一步根据抽样删去一部分看来不可能的总体，第二步再从余下总体中抽样，取含样本均值最大的那个总体为所需总体，我们用渐过分布方法得到了在所定规则下能选到正确总体的概率下界。特别对Ｌｏｇｉｓｔｉｃ总体计算了有关数值以及关于一次抽样的相对效。     

一种新的中位数排序集抽样下的对总体均值的Horvitz-Thompson估计

排序集抽样(RSS)是一种著名的抽样技术,它有许多变体,中位数排序集抽样(MRSS)就是其中一种.与简单随机抽样(SRS)相比,RSS在估计总体均值方面具有优势.然而,RSS及其变体的局限性在于,当给定样本大小n时,抽样过程中每次SRS的规模m只能是n或者n的因子.介绍了一种改进的中位数排序集抽样方法MRSS(m),它比原方法在抽样过程上有更多的选择.实验表明,采用新的抽样方法MRSS(m),可以提高Horvitz-Thompson(HT)估计量的估计效率,同时还降低了抽样成本.     

几个总体均值函数的鞍点逼近

本文发展了几个总体的均值向量的函数的尾部概率的鞍点逼近方法，并应用它于Bootstrap估计中，以代替Monte Carlo模拟，一些数值例子说明了其近似精度。     

有偏总体的EWMA均值控制图

基于总体分布有偏并假定总体分布未知情况下均值-极差控制图的控制限的研究结果,将其推广到EWMA均值控制图,给出总体分布有偏并假定总体分布未知情况下EWMA均值控制图的控制界限,并以质量特性值服从对数正态分布为例,给出EWMA均值控制图的控制效果的模拟分析.     

序约束下正态总体均值和方差极大似然估计的数值解法

本文讨论了k个独立正态总体的均值和方差同时在简单半序约束下的极大似然估计的求解问题,给出了计算极大估计的迭代算法,且证明该算法收敛。     

集团抽样不等概方法的均值估计及其性质

在集团抽样调查中，[1]和[2]给出了一般抽样方法及均值估计和它性质的论述，但未考虑各集团在总体中的地位对估计结果的影响，本文给出了集团抽样的不等概方法和均值的无偏估计，同时也给出了这种估计的方差及方差的无偏估计。     

One- and Two-Term Edgeworth Expansions for Finite Population Sample Mean. Exact Results. II

We prove the validity of one- and two-term Edgeworth expansions under optimal conditions (a Cramer-type smoothness condition and the minimal moment conditions) and provide precise bounds for the remainders of expansions. The bounds depend explicitly on the ratio p=N/n, where N denotes the sample size and n the population size, respectively.     

多阶段均值-半绝对偏差模糊投资组合优化研究

考虑交易成本和交易量限制,提出投资组合的收益率的隶属函数为梯形的多阶段均值-半绝对偏差可能性投资组合模型,并用自创算法——离散近似迭代法求解.其基本思路为:将连续型状态变量离散化,根据网络图的构造方法将上述模型转化多阶段赋权有向图;运用极大代数求出起点至终点的最长路程,即获得模型的一个可行解;以该可行解为基础,继续迭代直到前后两个可行解非常接近.文章还证明了该方法的线性收敛.最后,文章以一个具体的算例验证了该算法的有效性.     

平均样本间隔的性质及其在拍卖中的应用

研究了平均样本间隔E(Xk+1:n-Xk:n)的性质.证明了当X具有DRHR年龄性质时,E(Xk+1:n-Xk:n)关于样本容量n递减.而当X具有IFR年龄性质时,E(Xk+1:n-Xk:n)-E(Xk+2:n+1-Xk+1:n+1)非负.最后,讨论了主要结果在拍卖模型中的应用.     

Asymptotic Behavior of Sample Mean Direction for Spheres

In this note we consider some asymptotic properties of empirical mean direction on spheres. We do not require any symmetry for the underlying density. Thus our results provide the framework for an asymptotic inference regarding mean direction under very weak model assumptions. Mean direction is a specialization of the more general concept of mean location applicable to arbitrary (compact) submanifolds of Euclidean space, to which the methods of this paper could be applied.     

Two Sample Tests for Mean 3D Projective Shapes from Digital Camera Images

In this article, we extend mean 3D projective shape change in matched pairs to independent samples. We provide a brief introduction of projective shapes of spatial configurations obtained from their digital camera images, building on previous results of Crane and Patrangenaru (J Multivar Anal 102:225–237, 2011). The manifold of projective shapes of k-ads in 3D containing a projective frame at five given landmark indices has a natural Lie group structure, which is inherited from the quaternion multiplication. Here, given the small sample size, one estimates the mean 3D projective shape change in two populations, based on independent random samples of possibly different sizes using Efron’s nonparametric bootstrap. This methodology is applied in three relevant applications of analysis of 3D scenes from digital images: visual quality control, face recognition, and scene recognition.     

On a Characterization of the Gamma Distribution: The Independence of the Sample Mean and the Sample Coefficient of Variation

Let n 3 and let X ₁,...,X _n be positive i.i.d. random variables whose common distribution function f has a continuous p.d.f. Using earlier work of the present authors and a method due to Anosov for solving certain integro-functional equations, it is shown that the independence of the sample mean and the sample coefficient of variation is equivalent to that f is a gamma function. While the proof is of methodological interest, this conclusion can also be arrived at without any assumptions by appealing to the Laplace-Stieltjes transform, as in the Concluding Romark (Section 3).     

Mean Location and Sample Mean Location on Manifolds: Asymptotics, Tests, Confidence Regions

In a previous investigation we studied some asymptotic properties of the sample mean location on submanifolds of Euclidean space. The sample mean location generalizes least squares statistics to smooth compact submanifolds of Euclidean space. In this paper these properties are put into use. Tests for hypotheses about mean location are constructed and confidence regions for mean location are indicated. We study the asymptotic distribution of the test statistic. The problem of comparing mean locations for two samples is analyzed. Special attention is paid to observations on Stiefel manifolds including the orthogonal groupO(p) and spheresS^k−1, and special orthogonal groupsSO(p). The results also are illustrated with our experience with simulations.     

On the Spurious Correlation Between Sample Betas and Mean Returns

Abstract

Cornerstone asset pricing models, such as capital asset pricing model (CAPM) and arbitrage pricing theory (APT), yield theoretical predictions about the relationship between expected returns and exposure to systematic risk, as measured by beta(s). Numerous studies have investigated the empirical validity of these models. We show that even if no relationship holds between true expected returns and betas in the population, the existence of low-probability extreme outcomes induces a spurious correlation between the sample means and the sample betas. Moreover, the magnitude of this purely spurious correlation is similar to the empirically documented correlation, and the regression slopes and intercepts are very similar as well. This result does not necessarily constitute evidence against the theoretical asset pricing models, but it does shed new light on previous empirical results, and it points to an issue that should be carefully considered in the empirical testing of these models. The analysis points to the dangers of relying on simple least squares regression for drawing conclusions about the validity of equilibrium pricing models.     

样本总体分布判别方法及含钡硅酸盐玻璃类无机粉体的粒度分布

提出了判断样本观察值的总体分布类型的方法 ,即改进传统的应用概率纸判断的方法 .而是在Mathematica和 Matlab数学软件环境下 ,应用计算机在各种概率坐标系下作出散点图 ,当难于作出定性判断时 ,对散点图作回归的方差分析 ,给出定量的分析结果 .用此方法确定了牙科修复材料含钡硅酸盐玻璃类无机粉体粒度的概率密度函数为对数正态分布     

Estimation of the Common Mean of a Bivariate Normal Population

In this paper we discuss the problem of estimating the common mean of a bivariate normal population based on paired data as well as data on one of the marginals. Two double sampling schemes with the second stage sampling being either a simple random sampling (SRS) or a ranked set sampling (RSS) are considered. Two common mean estimators are proposed. It is found that under normality, the proposed RSS common mean estimator is always superior to the proposed SRS common mean estimator and other existing estimators such as the RSS regression estimator proposed by Yu and Lam (1997, Biometrics, 53, 1070–1080). The problem of estimating the mean Reid Vapor Pressure (RVP) of regular gasoline based on field and laboratory data is considered.