Combining Univariate Tests for Multivariate Location Problem

In this article, three methods of combining dependent univariate tests are studied. The Bahadur approximate efficiencies are derived under the asymptotic normal assumption. These procedures are applied to the multivariate location problem and compared with two Hotelling-type tests. A Monte Carlo study indicates that in certain cases the powers of the combination methods are much better than Hotelling's T ² and other multivariate nonparametric tests.     

Robust Likelihood Cross-Validation for Kernel Density Estimation

Likelihood cross-validation for kernel density estimation is known to be sensitive to extreme observations and heavy-tailed distributions. We propose a robust likelihood-based cross-validation method to select bandwidths in multivariate density estimations. We derive this bandwidth selector within the framework of robust maximum likelihood estimation. This method establishes a smooth transition from likelihood cross-validation for nonextreme observations to least squares cross-validation for extreme observations, thereby combining the efficiency of likelihood cross-validation and the robustness of least-squares cross-validation. We also suggest a simple rule to select the transition threshold. We demonstrate the finite sample performance and practical usefulness of the proposed method via Monte Carlo simulations and a real data application on Chinese air pollution.     

A partial score test for difference among heterogeneous populations

In event time data analysis, comparisons between distributions are made by the logrank test. When the data appear to contain crossing hazards phenomena, nonparametric weighted logrank statistics are usually suggested to accommodate different-weighted functions to increase the power. However, the gain in power by imposing different weights has its limits since differences before and after the crossing point may balance each other out. In contrast to the weighted logrank tests, we propose a score-type statistic based on the semiparametric-, heteroscedastic-hazards regression model of Hsieh [2001. On heteroscedastic hazards regression models: theory and application. J. Roy. Statist. Soc. Ser. B 63, 63–79.], by which the nonproportionality is explicitly modeled. Our score test is based on estimating functions derived from partial likelihood under the heteroscedastic model considered herein. Simulation results show the benefit of modeling the heteroscedasticity and power of the proposed test to two classes of weighted logrank tests (including Fleming–Harrington's test and Moreau's locally most powerful test), a Renyi-type test, and the Breslow's test for acceleration. We also demonstrate the application of this test by analyzing actual data in clinical trials.     

集聚效应、集聚效率与城市规模分布变化

摘　　要:本文从城市集聚效应的视角,分析我国城市规模分布的结构性变化的机制,在此基础上构建了包含集聚效应的城市总量生产函数的计量经济学模型,然后应用OLS方法估算我国不同规模等级城市的平均集聚效应指数和平均集聚效率指数．并对比分析其对城市规模分布变化的影响。本文的实证结果表明,平均集聚效率指数的高低与城市规模分布比重的增减相一致。     

统一涉外税制 改善投资环境——简析《外商投资企业和外国企业所得税法》的特点

本文通过对新老涉外税法的比较,总结出新税法的三大特点:即统一外商投资企业的纳税制度;扩大税收优惠,增强对外商的吸引力;增设反避税条款,加强税务管理。     

通过尘障后的激光束特征

从辐射亮度方程出发,推导了在大粒子近似条件下,激光束通过尘障以后约化通量密度和漫射通量密度的表达式,并在四个常用激光波长上作了数值计算.结果表明,当散射粒子浓度较大时,尘障后表面上的漫射通量密度通常比约化通量密度高很多,且散布在较宽的范围内.随着光束远离尘障,漫射通量密度迅速减小,约化通量密度重新占据主导地位.     

试论谭平山在“一大”前后的思想和活动

本文就谭平山“一大”前后研究和宣传马克思主义,建立和发展广东党的组织;创办学校、培养干部,建立工会组织,发展工人运动;建立社会主义青年团,推动青年运动的发展等几个方面作了论述。     

论统计理论研究方法体系

一、统计理论研究方法体系的提出　　在相当长的一段时间里,我国统计界在进行统计理论研究时虽有意无意地采用了一些研究方法,但是,这些研究方法基本上分散零乱的,没使之系统化,这也许是造成我国统计理论研究还比较落后的一个重要原因。随着市场经济的不断完善,统计理论研究的不断深入,人们发现我国统计理论研究在向新领域、新高度跨越时,现有的方法难以适应研究的需要,客观实际方面要求我们应不断地总结过去的研究方法,创建新的研究方法。因此,对统计理论研究方法本身的研究被提到议事日程。实际上,当今科学技术的飞跃进步,科…     

“未被观察到的经济”——范围、定义、类别和方法

如今,谈论“地下经济”的人似乎越来越多,但究竟何为“地下经济”？人们却似乎不能准确地加以识别和界定,以致常常把“地下经济”、“隐性经济”、“隐蔽经济”、“影子经济”、“非正规经济”、“非法经济”及“犯罪经济”等术语混为一谈。事实上,西方国家早就开始关注和研究这些经济现象了,并把它们统称为“未被观察到的经济”（ＮｏｎＯｂｓｅｒｖｅｄＥｃｏｎｏ－ｍｙ,以下简称ＮＯＥ）。近年来,由于这些经济现象日益增多,直接影响着各国ＧＤＰ估计的全面性和质量,进而影响到各国宏观经济政策的制订与实施效果,因此,不光是西…