On the robustness of least squares procedures in regression models

The criterion robustness of the standard likelihood ratio test (LRT) under the multivariate normal regression model and also the inference robustness of the same test under the univariate set up are established for certain nonnormal distributions of errors. Restricting attention to the normal distribution of errors in the context of univariate regression models, conditions on the design matrix are established under which the usual LRT of a linear hypothesis (under homoscedasticity of errors) remains valid if the errors have an intraclass covariance structure. The conditions hold in the case of some standard designs. The relevance of C. R. Rao's (1967 In Proceedings Fifth Berkeley Symposium on Math. Stat. and Prob., Vol. 1, pp. 355–372) and G. Zyskind's (1967, Ann. Math. Statist.38 1092–1110) conditions in this context is discussed.     

提高综合滤波器鉴别率的一种有效方法

提出一种提高综合滤波器鉴别率的有效方法，其做法是：对样本集在等相关峰条件下求解综合滤波器的同时，使样本集的互补样本满足零件相关峰条件，此方法把训练模式类同所有其它模式类在映射空间的距离拉大，有效地提高了综合滤波器的鉴别率，以取自同一手指纹为样本集，求解综合鉴别函数后，建立了指纹的实时模式识别系统，实验结果表明本文提出的改进方法对提高综合滤波器的鉴别率是非常有效的。     

Normalizing and variance stabilizing transformations for intraclass correlations

Summary A concept of normalizing transformations of statistics is constructed on the basis of the rate of convergence to normality. The concept is applied to derive a normalizing transformation of a maximum likelihood estimate of intraclass correlation coefficient in ap-variate normal sample. Numerical comparisons are made to examine whether the proposed transformation is efficient to achieve normality. The relationship between normalization and variance stabilization is also considered. The Institute of Statistical Mathematics     

k组多元自相关数据服从同一模型的假设检验

本文考虑了ｋ个多元同类自相关线性模型的回归系数和协方差阵相等的同时检验问题，得到了似然比检验统计量，统计量的矩及渐近中心分布。     

Simultaneous Estimation of Several Intraclass Correlation Coefficients

Based on shrinkage and preliminary test rules, various estimators are proposed for estimation of several intraclass correlation coefficients when independent samples are drawn from multivariate normal populations. It is demonstrated that the James-Stein type estimators are asymptotically superior to the usual estimators. Furthermore, it is also indicated through asymptotic results that none of the preliminary test and shrinkage estimators dominate each other, though they perform relatively well as compared to the classical estimator. The relative dominance picture of the estimators is presented. A Monte Carlo study is performed to appraise the properties of the proposed estimators for small samples.     

Construction,properties and statistical applications of positive definite intraclass matrix

Given a positive definite (p.d.) matrix with real entries, it is possible to construct a p.d. intraclass matrix whose diagonal and off-diagonal elements are chosen as the averages of the diagonal elements and off-diagonal elements of the former matrix. Exploiting the very special structure of the latter matrix various interesting propositions are established. Statistical applications of such matrices are surveyed.     

Inferences on interclass and intraclass correlations in multivariate familial data

Inference procedures for interelass and intraclass correlations are given in the multivariate context of familial data for which measurements are taken on more than one characteristic. Unified estimators are proposed based on a certain class of unbiased estimators of covariance matrices. Asymptotic distributions of the proposed estimators are derived under the assumption of multivariate normality. The results can be used to construct approximate confidence intervals and test procedures.Research supported by the Department of Statistics, the Pennsylvania State University and the Air Force Office of Scientific Research under Grant AFSO-88-0030.Institute of Statistical Mathematics     

Models with a Kronecker product covariance structure: Estimation and testing

In this article we consider a pq-dimensional random vector x distributed normally with mean vector θ and covariance matrix Λ assumed to be positive definite. On the basis of N independent observations on the random vector x, we want to estimate parameters and test the hypothesis H: Λ = Ψ ⊗ Σ, where Ψ = (ψ _ij ): q × q, ψ _qq = 1, and Σ = (σ _ij ): p × p, and Λ = (ψ _ij Σ), the Kronecker product of Ψ and Σ. That is instead of 1/2pq(pq + 1) parameters, it has only 1/2p(p + 1) + 1/2q(q + 1) − 1 parameters. A test based on the likelihood ratio is given to check if this model holds. And, when this model holds, we test the hypothesis that Ψ is a matrix with intraclass correlation structure. The maximum likelihood estimators (MLE) are obtained under the hypothesis as well as under the alternatives. Using these estimators the likelihood ratio tests (LRT) are obtained. One of the main objects of the paper is to show that the likelihood equations provide unique estimators.      

非独立计数资料的内部相关性研究

本研究探讨了非独立计数资料的内部相关性的测度方法。利用多平广义线性模型 ,导出了相应三种模型的家庭和地区内部相关系数公式 ,并用 1 992年四川省病毒性肝炎血清流行病学调查资料进行了实证性分析 ,结果符合实际。这说明本文有关非独立计数资料的内部相关系数的计算方法是合理的     

组内相关系数:定义辨析、估计方法与实际应用

“组内相关系数”正越来越多地被用于自然科学与社会科学诸领域,但国内外应用者对其定义与估计方法的理解尚有不足.其名称源于将“皮尔逊积矩相关”与对称表结合构成配对估计量的经典定义.而费希尔基于组间方差比重的新定义得益于哈里斯对配对估计量的简化.新定义在平衡数据下可由ANOVA法估计且与配对估计量渐近相等,故两种定义被统称为组内相关系数.在非平衡数据下有9个估计量可供选择,包括6个加权配对和3个方差成分类估计量.应用中需按观察变量是否符合正态分布假设等原则加以选择.本研究例解了方差成分类估计量的Stata命令.