《宋代登科总录》与宋代状元研究

《宋代登科总录》收录了大量宋代状元文献,通过统计分析可以确定,除118 位文科状元外,宋代还诞生了72位武科状元、12位贡士及第状元. 宋代文状元有近八成来自于低层官员与平民家庭,与唐代形成极大反差,折射出科举考试对整个社会政治的深刻影响. 宋代武科状元仕途不显,而文科状元中近六成曾在政府机构中担任宰执与侍从官等重要职务,这既是国家“右文”政策导向的结果,也验证了科举取士在人才流动方面的推动作用.     

Monitoring of autocorrelated general linear profiles

A collection of quality data represented by a functional relationship between response and explanatory variables is called a profile. In the literature, the errors of profiles are often assumed to be independent. However, quality data often exhibits time correlations in real applications. Therefore, in this paper, we investigate a general linear regression model with a between-profile autocorrelation. We propose a multivariate exponentially weighted moving average chart for monitoring shifts in the regression parameters, and an exponentially weighted moving average chart for monitoring shifts in the standard deviation. A simulation study reveals that our proposed schemes outperform competing existing schemes based on the average run length criterion. An example is used to illustrate the applicability of the proposed scheme.     

Preliminary phi-divergence test estimators for linear restrictions in a logistic regression model

The problem of estimation of the parameters in a logistic regression model is considered under multicollinearity situation when it is suspected that the parameter of the logistic regression model may be restricted to a subspace. We study the properties of the preliminary test based on the minimum ϕ -divergence estimator as well as in the ϕ -divergence test statistic. The minimum ϕ -divergence estimator is a natural extension of the maximum likelihood estimator and the ϕ -divergence test statistics is a family of the test statistics for testing the hypothesis that the regression coefficients may be restricted to a subspace.     

Performer-Level Systems Analysis

Abstract

A review of the Journal of Organizational Behavior Management(1992-2001) was conducted to determine how “systemic” the applied behavioral interventions were. Criteria for the term “systemic” in an organizational behavior context were derived from Rummler and Brache's (1995) Human Performance System (HPS). Six dependent measures derived from Rummler and Brache's HPS were used to evaluate the systemic nature of the interventions. The dependent variables were classified into one of three mutually exclusive categories: whether the variable was modified, discussed but not modified, or absent. The classification of variables was used to determine the degree to which an intervention was “systemic.” Results indicated that considerations of systemic factors were often modified and rarely merely discussed. A majority of the studies examined dealt with 2, 3, or 4 of the 6 systemic variables evaluated.     

略论科学通史课在高校通识教育中的地位和作用

科学通史课程凝练了各学科对自然界认识的精华,展现了科学发展与社会的互动关系,突出了创新思维方式培养的必要性与重大意义。通过分析科学通史课程教学在目前高校通识教育中的必要性、目的和意义,探讨了该课程在高校通识教育中的核心作用。     

欧共体竞争法适用共同利益服务原则的实践

《欧共体条约》的目标是实现在共同体内货物、人员、服务和资本的无障碍流动,必然要求肃清市场内外的限制性做法,包括迫使经济性公共服务引入竞争机制。“共同利益服务”原则已成为共同体意义上重要的公共服务原则,同时也是欧洲模式社会的一个主要组成部分。如今,某些共同经济利益服务已经通过适用欧盟竞争政策而属于市场开放的领域,但是它并没有包含所有的共同利益服务,特别是非经济服务是被排除的。这一点体现在欧共体委员会和欧共体法院的司法实践中。     

Multi-step forecasts from threshold ARMA models using asymmetric loss functions

The forecasts generation from nonlinear time series models is investigated under general loss functions. After presenting the main results and some relevant features of these functions, the Linex loss has been used to generate multi-step forecasts from threshold autoregressive moving average models showing their main properties and some results connected to a proper transformation of the forecast errors. A simulation exercise highlights interesting properties of the proposed predictors, both in terms of their bias and their distribution, further clarifying how the Linex predictor can be helpful in empirical applications.     

Estimation of parameterized spatio-temporal dynamic models

Spatio-temporal processes are often high-dimensional, exhibiting complicated variability across space and time. Traditional state-space model approaches to such processes in the presence of uncertain data have been shown to be useful. However, estimation of state-space models in this context is often problematic since parameter vectors and matrices are of high dimension and can have complicated dependence structures. We propose a spatio-temporal dynamic model formulation with parameter matrices restricted based on prior scientific knowledge and/or common spatial models. Estimation is carried out via the expectation–maximization (EM) algorithm or general EM algorithm. Several parameterization strategies are proposed and analytical or computational closed form EM update equations are derived for each. We apply the methodology to a model based on an advection–diffusion partial differential equation in a simulation study and also to a dimension-reduced model for a Palmer Drought Severity Index (PDSI) data set.     

国家语委"通用语料库·核心库"的词表提取及词汇构成分析

在真实语料中提取词表面临着许多技术与理论上的难点与困难,但它又有着特殊的价值."通用语料库"是国家语委组织研制的大型语料库,基本反映了现代汉语的语言面貌,完成对它的词表提取,其过程、做法及词表结果,都有着重要意义.机器分词时会遇到分词的正确性、加工精度的可容性、机器分词的强制性、机器分词的局限性等问题.源于真实语料的词表清楚反映出断代词汇由语言词和言语词两个层面构成,两个层面的词语之间有着互渗作用.源于真实语料的词表存在着书面语与口语的差异,不规范现象也较普遍存在,在词语的普遍性上与断代词汇有着相当的距离.     

Likelihood-based estimation for Gaussian MRFs

Markov random fields (MRFs) express spatial dependence through conditional distributions, although their stochastic behavior is defined by their joint distribution. These joint distributions are typically difficult to obtain in closed form, the problem being a normalizing constant that is a function of unknown parameters. The Gaussian MRF (or conditional autoregressive model) is one case where the normalizing constant is available in closed form; however, when sample sizes are moderate to large (thousands to tens of thousands), and beyond, its computation can be problematic. Because the conditional autoregressive (CAR) model is often used for spatial-data modeling, we develop likelihood-inference methodology for this model in situations where the sample size is too large for its normalizing constant to be computed directly. In particular, we use simulation methodology to obtain maximum likelihood estimators of mean, variance, and spatial-depencence parameters (including their asymptotic variances and covariances) of CAR models.