汉德祝愿语比较

祝愿语是一种民俗语言现象 ,是社会文明的重要标志之一。汉德祝愿语在用词、句法、文化背景等方面均存在共性与差异 ,在跨文化交际的过程中 ,尤其需要认清由于各自的文化背景和传统不同所造成的差异     

ASSESSING ERROR RATE ESTIMATORS: THE LEAVE-ONE-OUT METHOD RECONSIDERED

Many comparative studies of the estimators of error rates of supervised classification rules are based on inappropriate criteria. In particular, although they fix the Bayes error rate, their summary statistics aggregate a range of true error rates. This means that their conclusions about the performance of classification rules cannot be trusted. This paper discusses the general issues involved, and then focuses attention specifically on the leave-one-out estimator. The estimator is investigated in a simulation study, both in absolute terms and in comparison with a popular bootstrap estimator. An improvement to the leave-one-out estimator is suggested, but the bootstrap estimator appears to maintain superiority even when the criteria are adjusted.     

中国数字经济产业统计分类问题研究

数字经济在推动经济增长和转变人们生活方式方面发挥了重要作用,已成为推动中国经济高质量发展的“新引擎”。然而,中国数字经济统计研究明显滞后于数字经济发展实践,这不利于相关部门监测数字经济发展和科学制定政策。本文系统梳理了数字经济的概念演进以及经济合作与发展组织、美国经济分析局等国际组织和官方统计部门对数字经济相关产业的统计划分。结合中国已有相关统计分类标准,提出了中国数字经济产业统计分类,具体包括数字设备制造、数字信息传输、数字技术服务、数字内容与媒体、互联网应用及相关服务5个大类,共计22个中类、122个小类,并与国际上现有的相应产业分类进行了对比分析。本文可为官方统计机构建立数字经济产业统计分类标准、统计和发布相关统计数据提供理论参考。     

GEOMETRIC DECAY OF THE STEADY-STATE PROBABILITIES IN A QUASI-BIRTH-AND-DEATH PROCESS WITH A COUNTABLE NUMBER OF PHASES

A sufficient condition is proved for geometric decay of the steady-state probabilities in a quasi-birth-and-death process having a countable number of phases in each level. If there is a positive number η and positive vectors x = (x _i) and y = (y _j ) satisfying some equations and inequalities, the steady-state probability π _mi decays geometrically with rate η in the sense π _mi ～ cη ^m x _i as m → ∞. As an example, the result is applied to a two-queue system with shorter queue discipline.     

Tree‐Based Logistic Regression Approach for Work Zone Casualty Risk Assessment

This study presents a tree‐based logistic regression approach to assessing work zone casualty risk, which is defined as the probability of a vehicle occupant being killed or injured in a work zone crash. First, a decision tree approach is employed to determine the tree structure and interacting factors. Based on the Michigan M‐94\I‐94\I‐94BL\I‐94BR highway work zone crash data, an optimal tree comprising four leaf nodes is first determined and the interacting factors are found to be airbag, occupant identity (i.e., driver, passenger), and gender. The data are then split into four groups according to the tree structure. Finally, the logistic regression analysis is separately conducted for each group. The results show that the proposed approach outperforms the pure decision tree model because the former has the capability of examining the marginal effects of risk factors. Compared with the pure logistic regression method, the proposed approach avoids the variable interaction effects so that it significantly improves the prediction accuracy.     

ASYMPTOTIC DISTRIBUTIONS OF SEASONAL UNIT ROOT TESTS: A UNIFYING APPROACH

ABSTRACT

This paper adopts a unified approach to the derivation of the asymptotic distributions of various seasonal unit root tests. The procedures considered are those of Dickey et al. [DHF], Kunst, Hylleberg et al. [HEGY], Osborn et al. [OCSB], Ghysels et al. [GHL] and Franses. This unified approach shows that the asymptotic distributions of all these test statistics are functions of the same vector of Brownian motions. The Kunst test and the overall HEGY F-test are, indeed, equivalent both asymptotically and in finite samples, while the Franses and GHL tests are shown to have equivalent parameterizations. The OCSB and DHF test regressions are viewed as restricted forms of the Kunst-HEGY regressions, and these restrictions may have non-trivial asymptotic implications.     

Dealing with label switching in mixture models

In a Bayesian analysis of finite mixture models, parameter estimation and clustering are sometimes less straightforward than might be expected. In particular, the common practice of estimating parameters by their posterior mean, and summarizing joint posterior distributions by marginal distributions, often leads to nonsensical answers. This is due to the so-called 'label switching' problem, which is caused by symmetry in the likelihood of the model parameters. A frequent response to this problem is to remove the symmetry by using artificial identifiability constraints. We demonstrate that this fails in general to solve the problem, and we describe an alternative class of approaches, relabelling algorithms , which arise from attempting to minimize the posterior expected loss under a class of loss functions. We describe in detail one particularly simple and general relabelling algorithm and illustrate its success in dealing with the label switching problem on two examples.     

Understanding the role of facial asymmetry in human face identification

Face recognition has important applications in forensics (criminal identification) and security (biometric authentication). The problem of face recognition has been extensively studied in the computer vision community, from a variety of perspectives. A relatively new development is the use of facial asymmetry in face recognition, and we present here the results of a statistical investigation of this biometric. We first show how facial asymmetry information can be used to perform three different face recognition tasks—human identification (in the presence of expression variations), classification of faces by expression, and classification of individuals according to sex. Initially, we use a simple classification method, and conduct a feature analysis which shows the particular facial regions that play the dominant role in achieving these three entirely different classification goals. We then pursue human identification under expression changes in greater depth, since this is the most important task from a practical point of view. Two different ways of improving the performance of the simple classifier are then discussed: (i) feature combinations and (ii) the use of resampling techniques (bagging and random subspaces). With these modifications, we succeed in obtaining near perfect classification results on a database of 55 individuals, a statistically significant improvement over the initial results as seen by hypothesis tests of proportions.     

城市园林特殊绿化空间技术的现状与发展对策

城市园林除了对自然地大面积的利用外,还可以对特殊绿化空间进行利用。城市特殊绿化空间是指城市各类建筑和构筑物所形成的空间和表面,植物可以在自然条件下或采取人工措施下生长。提出了以生境为主,结合建筑物的形态特征的城市园林特殊空间分类方法。随着生态建筑的提出,城市特殊绿化空间绿化的发展更加趋于生态化与自然化,并在营造水平上趋于设施化与工艺化。     

Bias Correction in the Dynamic Panel Data Model with a Nonscalar Disturbance Covariance Matrix

Abstract

Approximation formulae are developed for the bias of ordinary and generalized Least Squares Dummy Variable (LSDV) estimators in dynamic panel data models. Results from Kiviet [Kiviet, J. F. (1995), on bias, inconsistency, and efficiency of various estimators in dynamic panel data models, J. Econometrics68:53–78; Kiviet, J. F. (1999), Expectations of expansions for estimators in a dynamic panel data model: some results for weakly exogenous regressors, In: Hsiao, C., Lahiri, K., Lee, L‐F., Pesaran, M. H., eds., Analysis of Panels and Limited Dependent Variables, Cambridge: Cambridge University Press, pp. 199–225] are extended to higher‐order dynamic panel data models with general covariance structure. The focus is on estimation of both short‐ and long‐run coefficients. The results show that proper modelling of the disturbance covariance structure is indispensable. The bias approximations are used to construct bias corrected estimators which are then applied to quarterly data from 14 European Union countries. Money demand functions for M1, M2 and M3 are estimated for the EU area as a whole for the period 1991: I–1995: IV. Significant spillovers between countries are found reflecting the dependence of domestic money demand on foreign developments. The empirical results show that in general plausible long‐run effects are obtained by the bias corrected estimators. Moreover, finite sample bias, although of moderate magnitude, is present underlining the importance of more refined estimation techniques. Also the efficiency gains by exploiting the heteroscedasticity and cross‐correlation patterns between countries are sometimes considerable.