Admissibility for linear estimators of regression coefficient in a general Gauss–Markoff model under balanced loss function

A generalization of Zellner's balanced loss function is proposed according to unified theory of least squares under a general Gauss–Markoff model. Admissibility of linear estimators is investigated under the balanced loss function. And necessary and sufficient conditions that linear estimators are admissible in a class of homogeneous and nonhomogeneous linear estimators are obtained, respectively.     

Estimation of the mean of a spherically symmetric distribution with constraints on the norm

The authors consider the problem of estimating, under quadratic loss, the mean of a spherically symmetric distribution when its norm is supposed to be known and when a residual vector is available. They give a necessary and sufficient condition for the optimal James‐Stein estimator to dominate the usual estimator. Various examples are given that are not necessarily variance mixtures of normal distributions. Consideration is also given to an alternative class of robust James‐Stein type estimators that take into account the residual vector. A more general domination condition is given for this class.     

空间多曲线钢索预应力摩擦损失试验研究

在公路钢筋混凝土及预应力桥涵设计规范提出的平面曲线钢索预应力摩擦损失计算公式的基础上，提出了空间多曲线型钢索预应力摩擦损失的计算方法。     

略论汉寿明清时代的水患

汉寿宋元以前水灾并不多 ,明清时期泛滥成灾。究其原因 ,除汉寿地处洞庭湖盆最低洼地带 ,沅水水流量、降雨量极为充沛等自然因素外 ,主要是因为植被的破坏、水土的流失和荆江的虎渡、藕池、松滋三口此时期冲成以及明清大规模的围湖筑垸等人为因素造成     

乡镇政府权威流失问题的实证分析

乡镇政府是农村基层政权组织,是党和政府联系广大农民的桥梁和纽带,担负着发展农村经济、服务农村百姓、稳定农村社会的重要职责。但是,当前的乡镇政府与以前相比,其权威有不小的流失,尤其进入＂后农业税时代＂。严重的地方,动员失去号召力,协调缺乏驾驭力,管理失去约束力,发展缺乏凝聚力,治安失去震慑力。因此,对乡镇政府权威流失状况进行深入的考察和分析,显得尤为紧迫、必要和意义深远。     

Therapy with Infertile Heterosexual Couples: It’s Not About Gender—Or is it?

In spite of medical data that show males are equal to their female partners as a source of a heterosexual couple’s infertility, therapists face many unanswered questions about the extent to which gender influences each partner’s infertility experience in American culture. How is “hers” different from “his?” To what extent should the therapist strive to help the couple define the infertility issue as “ours”? This article explores how the therapist can elicit and be sensitive to gender issues while fostering resilience in the infertile couple.     

项目投资效益审计的不确定性分析

项目投资效益审计中经常存在许多不确定性因素，对这些因素进行不确定性分析，才能找出影响项目投资的重要因素，为管理决策提供依据。在介绍效益审计概念与不确定性产生原因的基础上讲述了盈亏平衡点与敏感性分析项目在投资效益审计的应用。     

The admissible minimax estimator in Gauss–Markov model under a balanced loss function

In this paper, we investigate the admissible minimax estimator (AME) of regression coefficient in Gauss–Markov model under a balanced loss function. In the class of homogeneous linear estimators, we obtain the AME under two occasions, respectively. We also prove that the AME is a shrinkage estimator of the best linear unbiased estimator (BLUE). Furthermore, we prove that the AME dominates the BLUE under certain conditions.     

On Bayes Linear Unbiased Estimator Under the Balanced Loss Function

In this paper, the Bayes linear unbiased estimator (Bayes LUE) is derived under the balanced loss function. Moreover, the superiority of Bayes LUE over ordinary least square estimator is studied under the mean square error matrix criterion and Pitman closeness criterion. Furthermore, we compare Bayes LUE under the balanced loss function with Bayes LUE under the quadratic loss function.     

Prediction Error Estimation Under Bregman Divergence for Non-Parametric Regression and Classification

Abstract.  Prediction error is critical to assess model fit and evaluate model prediction. We propose the cross-validation (CV) and approximated CV methods for estimating prediction error under the Bregman divergence (BD), which embeds nearly all of the commonly used loss functions in the regression, classification procedures and machine learning literature. The approximated CV formulas are analytically derived, which facilitate fast estimation of prediction error under BD. We then study a data-driven optimal bandwidth selector for local-likelihood estimation that minimizes the overall prediction error or equivalently the covariance penalty. It is shown that the covariance penalty and CV methods converge to the same mean-prediction-error-criterion. We also propose a lower-bound scheme for computing the local logistic regression estimates and demonstrate that the algorithm monotonically enhances the target local likelihood and converges. The idea and methods are extended to the generalized varying-coefficient models and additive models.