How do countries choose their monetary policy frameworks?

This paper investigates the determinants of countries’ choices of monetary policy framework. A brief narrative focused on groupings of countries motivates an econometric analysis which draws on previous work on the determinants of exchange rate regimes, bringing in standard factors as well as the trade networks of potential anchor currency blocs and the financial market depth that are emphasised in the narrative. The model turns out to be able to predict three quarters of countries’ choices, and there is no obvious systematic pattern in the errors. The results have important implications for how countries should choose their monetary policy frameworks.     

国内外二语词汇深度研究综述

近十几年来国内外研究者开始将词汇研究的重点从宽度或词汇量的研究转向对词汇深度或词质量的研究。和产出性词汇相比 ,接受性词汇习得具有明显的“超出”现象 ;词汇知识习得过程存在一定的发展模式 ,如学习初期词义发展较快 ,中高级阶段派生、搭配等发展较快 ;词汇深度和广度与语言综合能力尤其是阅读能力关系密切     

Multivariate outlier detection in incomplete survey data: the epidemic algorithm and transformed rank correlations

Summary.  As a part of the EUREDIT project new methods to detect multivariate outliers in incomplete survey data have been developed. These methods are the first to work with sampling weights and to be able to cope with missing values. Two of these methods are presented here. The epidemic algorithm simulates the propagation of a disease through a population and uses extreme infection times to find outlying observations. Transformed rank correlations are robust estimates of the centre and the scatter of the data. They use a geometric transformation that is based on the rank correlation matrix. The estimates are used to define a Mahalanobis distance that reveals outliers. The two methods are applied to a small data set and to one of the evaluation data sets of the EUREDIT project.     

叛逆女性的性格悲剧--《雷雨》中繁漪形象的深度阐解

《雷雨》中的繁漪是具有鲜明特色和复杂蕴涵的叛逆女性形象，其鲜明特色在于独特性的雷雨性格，其复杂蕴涵在于人性建构中的理性因素与非理性因素和个体生命力中的创造性力量与破坏性力量的相兼相制，因而深切地显现出人性的深度。     

Resampling-based Classification Using Depth for Functional Curves

The depths, which have been used to detect outliers or to extract a representative subset, can be applied to classification. We propose a resampling-based classification method based on the fact that resampling techniques yield a consistent estimator of the distribution of a statistic. The performance of this method was evaluated with eight contaminated models in terms of Correct Classification Rates (CCRs), and the results were compared with other known methods. The proposed method consistently showed higher average CCRs and 4% higher CCR at the maximum compared to other methods. In addition, this method was applied to Berkeley data. The average CCRs were between 0.79 and 0.85.     

对我国高等院校“专接本”教育模式的反思

本文阐明"专接本"教育的双重属性,表明"专接本"教育的定位内涵,提出"专接本"教育区别于普通本科教育、也有别于专科职业教育,却是职业教育的接续和深化。强调变革现行"专接本"教育的培养方案、师资队伍、教学评价系统、教学管理机制。     

On smoothness of Tukey depth contours

The smoothness of Tukey depth contours is a regularity condition often encountered in asymptotic theory, among others. This condition ensures that the Tukey depth fully characterizes the underlying multivariate probability distribution. In this paper we demonstrate that this regularity condition is rarely satisfied. It is shown that even well-behaved probability distributions with symmetrical, smooth and (strictly) quasi-concave densities may have non-smooth Tukey depth contours, and that the smoothness behaviour of depth contours is fairly unpredictable.     

Testing Treatment-Covariate Interaction in a Nonparametric Analysis of Covariance Model

We consider a recently introduced nonparametric model for Analysis of Covariance and derive an asymptotic test for interaction between covariate and treatment. Furthermore, we suggest data depth techniques to obtain joint confidence regions for the covariate effects in this model.

The finite sample behavior of the asymptotic method is evaluated in simulations. Application of the procedures is illustrated using an epileptic seizures and chemotherapy data set.     

Data depth and correlation

Summary: We describe depth–based graphical displays that show the interdependence of multivariate distributions. The plots involve one–dimensional curves or bivariate scatterplots, so they are easier to interpret than correlation matrices. The correlation curve, modelled on the scale curve of Liu et al. (1999), compares the volume of the observed central regions with the volume under independence. The correlation DD–plot is the scatterplot of depth values under a reference distribution against depth values under independence. The area of the plot gives a measure of distance from independence. Correlation curve and DD-plot require an independence model as a baseline: Besides classical parametric specifications, a nonparametric estimator, derived from the randomization principle, is used. Combining data depth and the notion of quadrant dependence, quadrant correlation trajectories are obtained which allow simultaneous representation of subsets of variables. The properties of the plots for the multivariate normal distribution are investigated. Some real data examples are illustrated. *This work was completed with the support of Ca Foscari University.     

Regression Depth with Censored and Truncated Data

Abstract

In this article, we consider the problem of estimating regression coefficients for a linear model with censored and truncated data based on regression depth. Any line can be given a rank using regression depth and the deepest regression line is the line with the maximum regression depth. We propose a method to define the regression depth of a line in the presence of censoring and truncation. We show how the proposed regression performs through analyzing Stanford heart transplant data and AIDS incubation data.