Adaptive bootstrap tests and its competitors in the c-sample scale problem

This paper deals with a study of different types of tests for the two-sided c-sample scale problem. We consider the classical parametric test of Bartlett [M.S. Bartlett, Properties of sufficiency and statistical tests, Proc. R. Stat. Soc. Ser. A. 160 (1937), pp. 268–282] several nonparametric tests, especially the test of Fligner and Killeen [M.A. Fligner and T.J. Killeen, Distribution-free two-sample tests for scale, J. Amer. Statist. Assoc. 71 (1976), pp. 210–213], the test of Levene [H. Levene, Robust tests for equality of variances, in Contribution to Probability and Statistics, I. Olkin, ed., Stanford University Press, Palo Alto, 1960, pp. 278–292] and a robust version of it introduced by Brown and Forsythe [M.B. Brown and A.B. Forsythe, Robust tests for the equality of variances, J. Amer. Statist. Assoc. 69 (1974), pp. 364–367] as well as two adaptive tests proposed by Büning [H. Büning, Adaptive tests for the c-sample location problem – the case of two-sided alternatives, Comm. Statist.Theory Methods. 25 (1996), pp. 1569–1582] and Büning [H. Büning, An adaptive test for the two sample scale problem, Nr. 2003/10, Diskussionsbeiträge des Fachbereich Wirtschaftswissenschaft der Freien Universität Berlin, Volkswirtschaftliche Reihe, 2003]. which are based on the principle of Hogg [R.V. Hogg, Adaptive robust procedures. A partial review and some suggestions for future applications and theory, J. Amer. Statist. Assoc. 69 (1974), pp. 909–927]. For all the tests we use Bootstrap sampling strategies, too. We compare via Monte Carlo Methods all the tests by investigating level α and power β of the tests for distributions with different strength of tailweight and skewness and for various sample sizes. It turns out that the test of Fligner and Killeen in combination with the bootstrap is the best one among all tests considered.     

关于多元函数的极值

建立了ｋ次齐次函数的正（负）定概念，得到了多元函数的极值判定定理     

A unified view on skewed distributions arising from selections

Parametric families of multivariate nonnormal distributions have received considerable attention in the past few decades. The authors propose a new definition of a selection distribution that encompasses many existing families of multivariate skewed distributions. Their work is motivated by examples that involve various forms of selection mechanisms and lead to skewed distributions. They give the main properties of selection distributions and show how various families of multivariate skewed distributions, such as the skew‐normal and skew‐elliptical distributions, arise as special cases. The authors further introduce several methods of constructing selection distributions based on linear and nonlinear selection mechanisms.     

Using the studentized range to assess kurtosis

Because it is easy to compute from three common statistics (minimum, maximum, standard deviation) the studentized range is a useful test for non-normality when the original data are unavailable. For samples from symmetric populations, the studentized range allows an assessment of kurtosis with Type I and II error rates similar to those obtained from the moment coefficients.     

On describing multivariate skewed distributions: A directional approach

Most multivariate measures of skewness in the literature measure the overall skewness of a distribution. These measures were designed for testing the hypothesis of distributional symmetry; their relevance for describing skewed distributions is less obvious. In this article, the authors consider the problem of characterizing the skewness of multivariate distributions. They define directional skewness as the skewness along a direction and analyze two parametric classes of skewed distributions using measures based on directional skewness. The analysis brings further insight into the classes, allowing for a more informed selection of classes of distributions for particular applications. The authors use the concept of directional skewness twice in the context of Bayesian linear regression under skewed error: first in the elicitation of a prior on the parameters of the error distribution, and then in the analysis of the skewness of the posterior distribution of the regression residuals.     

Invariant tests for multivariate normality: a critical review

d -dimensional random vector X is some nondegenerate d-variate normal distribution, on the basis of i.i.d. copies X ₁, ..., X _x of X. Particular emphasis is given to progress that has been achieved during the last decade. Furthermore, we stress the typical diagnostic pitfall connected with purportedly ‘directed’ procedures, such as tests based on measures of multivariate skewness. Received: April 30, 2001; revised version: October 30, 2001     

论传播场的基本特征

传播场是传播模式研究史上最具现代性的内容之一。以自然场的观点观照传播过程,以口语这一主要的和基本的传播媒介进行分析,可以发现传播场在基本方面具有传播主体的两极性、传播主体在传播实践中所受到的多维制约力、制约力具有方向性和可变性、传播主体与媒介具有同质特征以及主体和媒介具有可观察的个性和共性的二象性等与自然场基本同构的特征。     

金融资产收益非对称性分析

滑动分块自助法(moving-block bootstrap)是一种适合相依时间序列的再抽样方法,与传统的非对称性检验法相比,它能有效地拟合统计量的抽样分布,这是因为传统的非对称性检验均假设收益序列独立同分布,与大多数金融资产收益的统计特征不符;利用滑动分块自助法对中国股市指数进行实证分析可以知道,在“熊市”期间,收益显著右偏,而在“牛市”期间,非对称性不明显。由于金融资产收益的非对称性是影响投资组合、资产定价的重要因素,因此在金融理论与实践中具有重要意义。     

论主权民族在“族裔同质国家”的构建

主权民族就是"享有国家主权的民族",与"国族"、"政治民族"等概念具有相同的外延和内涵,只是侧重点不同。"族裔同质国家"构建主权民族有"国族一体式构建"、"代表式构建"和"共同创设式构建"三种方式。     

The wrapped skew-normal distribution on the circle

The wrapped skew-normal distribution is proposed as a model for circular data. Basic results for the distribution are established and estimation for a circular parametrisation of it considered. Procedures based on the sample second central sine moment for testing for departures from three important limiting cases of the distribution are described. The model and some new inferential techniques are applied to directional data from a study into bird migration.