On an asymptotic relative efficiency concept based on expected volumes of confidence regions

ABSTRACT

The paper deals with an asymptotic relative efficiency concept for confidence regions of multidimensional parameters that is based on the expected volumes of the confidence regions. Under standard conditions the asymptotic relative efficiencies of confidence regions are seen to be certain powers of the ratio of the limits of the expected volumes. These limits are explicitly derived for confidence regions associated with certain plugin estimators, likelihood ratio tests and Wald tests. Under regularity conditions, the asymptotic relative efficiency of each of these procedures with respect to each one of its competitors is equal to 1. The results are applied to multivariate normal distributions and multinomial distributions in a fairly general setting.     

Modern likelihood inference for the maximum/minimum of a bivariate normal vector

ABSTRACT

We consider the use of modern likelihood asymptotics in the construction of confidence intervals for the parameter which determines the skewness of the distribution of the maximum/minimum of an exchangeable bivariate normal random vector. Simulation studies were conducted to investigate the accuracy of the proposed methods and to compare them to available alternatives. Accuracy is evaluated in terms of both coverage probability and expected length of the interval. We furthermore illustrate the suitability of our proposals by means of two data sets, consisting of, respectively, measurements taken on the brains of 10 mono-zygotic twins and measurements of mineral content of bones in the dominant and non-dominant arms for 25 elderly women.     

Confidence interval estimation and hypothesis testing for a common correlation coefficient

Several procedures have been proposed for testing the hypothesis that all off-diagonal elements of the correlation matrix of a multivariate normal distribution are equal. If the hypothesis of equal correlation can be accepted, it is then of interest to estimate and perhaps test hypotheses for the common correlation. In this paper, two versions of five different test statistics are compared via simulation in terms of adequacy of the normal approximation, coverage probabilities of confidence intervals, control of Type I error, and power. The results indicate that two test statistics based on the average of the Fisher z-transforms of the sample correlations should be used in most cases. A statistic based on the sample eigenvalues also gives reasonable results for confidence intervals and lower-tailed tests.     

The Common Assessment Framework form 9 years on: a creative process

Legislation within England states that local authorities should provide services for all those families in need. However, research has identified that regardless of the introduction of strategies to identify need and enhance family support, ongoing barriers to services adhere. Taking a social constructionist approach, this study explored professionals' experiences of the use of the Common Assessment Framework form. Data were collected in four different local authorities in two phases. Forty‐one professionals from a variety of agencies took part in semi‐structured interviews. Data were analyzed thematically. Findings demonstrate that the professionals experienced difficulties in working through the Common Assessment Framework process, for example, in completing the form and engaging families. This situation led to the more experienced and knowledgeable professionals utilising creative ways to successfully navigate the ‘referral process’. Such creative working practices included the terminology used to complete the form and how the process was ‘sold’ to parents, so that they could be in a better position to engage parents and complete the Common Assessment Framework form. Because of this, more experienced professionals seem to be able to accelerate the referral process in order to access much needed support services for children and young people.     

Model-based clustering of multivariate skew data with circular components and missing values

Motivated by classification issues that arise in marine studies, we propose a latent-class mixture model for the unsupervised classification of incomplete quadrivariate data with two linear and two circular components. The model integrates bivariate circular densities and bivariate skew normal densities to capture the association between toroidal clusters of bivariate circular observations and planar clusters of bivariate linear observations. Maximum-likelihood estimation of the model is facilitated by an expectation maximization (EM) algorithm that treats unknown class membership and missing values as different sources of incomplete information. The model is exploited on hourly observations of wind speed and direction and wave height and direction to identify a number of sea regimes, which represent specific distributional shapes that the data take under environmental latent conditions.     

论高师体育教育专业健美操普修课多元化发展

从健美操运动发展的实际需要出发,针对目前高等师范院校体育教育专业传统健美操普修课教学所存在的问题,提出了根据社会需求的多样化走多元化发展道路的改革思路,并从课程的多元化发展设计的角度,分别就课程目标的多元化、教学途径多边化、授课类型多样化、教学内容多样化、教学评价综合化等进行了阐述。     

Selecting the normal population with the smallest variance: A restricted subset selection rule

Consider k( ? 2) normal populations whose means are all known or unknown and whose variances are unknown. Let σ²_[1] ? ??? ? σ_[k]² denote the ordered variances. Our goal is to select a non empty subset of the k populations whose size is at most m(1 ? m ? k ? 1) so that the population associated with the smallest variance (called the best population) is included in the selected subset with a guaranteed minimum probability P* whenever σ²_[2]/σ_[1]² ? δ* > 1, where P* and δ* are specified in advance of the experiment. Based on samples of size n from each of the populations, we propose and investigate a procedure called R_BCP. We also derive some asymptotic results for our procedure. Some comparisons with an earlier available procedure are presented in terms of the average subset sizes for selected slippage configurations based on simulations. The results are illustrated by an example.     

A simple algorithm for calculating values for folded normal distribution

Folded normal distribution originates from the modulus of normal distribution. In the present article, we have formulated the cumulative distribution function (cdf) of a folded normal distribution in terms of standard normal cdf and the parameters of the mother normal distribution. Although cdf values of folded normal distribution were earlier tabulated in the literature, we have shown that those values are valid for very particular situations. We have also provided a simple approach to obtain values of the parameters of the mother normal distribution from those of the folded normal distribution. These results find ample application in practice, for example, in obtaining the so-called upper and lower α-points of folded normal distribution, which, in turn, is useful in testing of the hypothesis relating to folded normal distribution and in designing process capability control chart of some process capability indices. A thorough study has been made to compare the performance of the newly developed theory to the existing ones. Some simulated as well as real-life examples have been discussed to supplement the theory developed in this article. Codes (generated by R software) for the theory developed in this article are also presented for the ease of application.     

历史不一定是发展史———中国古代都城形态史的解构

以往的研究认为中国古代都城城市形态的历史是一种前后相继的发展史，使用的主要研究方法就是对城市形态进行相似性比较，但这种方法在逻辑上存在根本性的问题，因此其结论是值得质疑的。基于对这一问题的研究，我们可以进一步认为，历史并不一定就是事物、事件之间有着密切联系、存在发展阶段以及变化规律可循的“发展史”，而可能只是由一些不存在密切联系，只是在时间上具有先后顺序的同类对象构成的历史。     

大芦家地区东二1亚段砂体微相纵横向分布研究

大芦家地区渐新统东二1亚段主要由三角洲前缘亚相组成,发育的微相类型包括河口坝、水下分流河道、水下决口扇及天然堤、远砂坝、席状砂、分流间湾等,它们在纵横向上表现出多次复合,多次叠加的特征,且各微相的界限和单砂层的界限并不一致;所有这些微相在垂向上的沉积序列可分为均一型、垂向减小型和垂向增大型三类;此外,该区三角洲体系沉积物源主要由河流从西北方向搬运而来,属高建设性的河控型三角洲,其平面呈朵状向东南方或南方延伸,其微相模式的特点是水下分流河道和河口坝沉积位于中心,其他微相分布在它们的外缘。