关于“建设生态文明”提出的依据及实现的途径

党的十七大适应国内外形势的新变化，顺应各族人民过上更好生活的新期待，提出了实现全面建设小康社会奋斗目标的新要求，并首次将“建设生态文明”写入报告，这是我们党科学发展、和谐发展理念的一次升华。而探讨生态文明形成的理论依据、现实依据以及建设生态文明的实现途径，对理解和落实十七大报告具有一定的借鉴作用。     

Loss functions for estimation of extrema with an application to disease mapping

It is often of interest to find the maximum or near maxima among a set of vector‐valued parameters in a statistical model; in the case of disease mapping, for example, these correspond to relative‐risk “hotspots” where public‐health intervention may be needed. The general problem is one of estimating nonlinear functions of the ensemble of relative risks, but biased estimates result if posterior means are simply substituted into these nonlinear functions. The authors obtain better estimates of extrema from a new, weighted ranks squared error loss function. The derivation of these Bayes estimators assumes a hidden‐Markov random‐field model for relative risks, and their behaviour is illustrated with real and simulated data.     

元认知与大学英语网络自主学习

目前我们汉译英的课堂教学模式过于简单且效率低下,本文提出了一种针对低学业成就者的、基于学习策略培训的汉译英SB I教学模式,从汉语语义结构分析、英语句子结构定型、英语词汇选择以及检查核对等多方面尝试将汉译英学习策略的培训渗透到汉译英的课堂教学活动中,以期提高这些学习者的汉译英技能,帮助他们掌握必要的语言学习策略,培养他们的自主学习能力,改善课堂教学效果。     

理工科大学素质教育中的中国民族音乐教育

艺术素质教育在古往今来的教育中都承担着重要的角色。中国民族音乐作为集艺术性与民族性为一体的音乐艺术形式,在世界音乐艺术领域占有重要的地位。通过不同的艺术教育途径,发扬和传承中国民族音乐,让更多的理工科大学生了解和热爱中国民族音乐,提高自身音乐修养,最终达到专业与艺术的完美融合。     

German family policy at the crossroads: analysing the impact of parental leave reform through simulation

Comparative studies of welfare reforms encounter two problems. First, the counterfactual problem is that in the real world schemes and their reforms do not coexist simultaneously and are hard to compare. Second, the contextual problem derives from the absence of comparable measures for change. Microsimulation helps to overcome these problems. It compares policy options – actual reforms or reform plans – simultaneously and provides a comparable measure: the disposable income of model families. This article uses a type–case approach to investigate recent reforms of the German parental leave benefit. Simulation makes those reforms comparable over time and across countries. Results show that the profile of the German scheme is changing from 'general family' towards 'dual-earner' support. Furthermore, the recent reforms make the German scheme converge towards the Swedish leave scheme. The recent reforms introduce a new concept of fairness and a focus on gender equality to German family policies.     

BAYESIAN SUBSET SELECTION AND MODEL AVERAGING USING A CENTRED AND DISPERSED PRIOR FOR THE ERROR VARIANCE

This article proposes a new data‐based prior distribution for the error variance in a Gaussian linear regression model, when the model is used for Bayesian variable selection and model averaging. For a given subset of variables in the model, this prior has a mode that is an unbiased estimator of the error variance but is suitably dispersed to make it uninformative relative to the marginal likelihood. The advantage of this empirical Bayes prior for the error variance is that it is centred and dispersed sensibly and avoids the arbitrary specification of hyperparameters. The performance of the new prior is compared to that of a prior proposed previously in the literature using several simulated examples and two loss functions. For each example our paper also reports results for the model that orthogonalizes the predictor variables before performing subset selection. A real example is also investigated. The empirical results suggest that for both the simulated and real data, the performance of the estimators based on the prior proposed in our article compares favourably with that of a prior used previously in the literature.     

THE CHOICE BETWEEN SETS OF REGRESSORS

This paper examines the choice of critical values for testing both non-sequential and nested sequential sets of constraints in the standard linear regression model. Modest increases in (e.g.) t-ratio critical values relative to their one-off values are often sufficient to maintain proper size. A Bayesian decision-theoretic approach, highlighted by the Schwarz (1978) criterion, provides a framework for deriving consistency and asymptotic local power properties of both forms of testing (data mining) algorithms.     

Bayes linear analysis for graphical models: The geometric approach to local computation and interpretive graphics

This paper concerns the geometric treatment of graphical models using Bayes linear methods. We introduce Bayes linear separation as a second order generalised conditional independence relation, and Bayes linear graphical models are constructed using this property. A system of interpretive and diagnostic shadings are given, which summarise the analysis over the associated moral graph. Principles of local computation are outlined for the graphical models, and an algorithm for implementing such computation over the junction tree is described. The approach is illustrated with two examples. The first concerns sales forecasting using a multivariate dynamic linear model. The second concerns inference for the error variance matrices of the model for sales, and illustrates the generality of our geometric approach by treating the matrices directly as random objects. The examples are implemented using a freely available set of object-oriented programming tools for Bayes linear local computation and graphical diagnostic display.     

Designing and integrating composite networks for monitoring multivariate gaussian pollution fields

Networks of ambient monitoring stations are used to monitor environmental pollution fields such as those for acid rain and air pollution. Such stations provide regular measurements of pollutant concentrations. The networks are established for a variety of purposes at various times so often several stations measuring different subsets of pollutant concentrations can be found in compact geographical regions. The problem of statistically combining these disparate information sources into a single 'network' then arises. Capitalizing on the efficiencies so achieved can then lead to the secondary problem of extending this network. The subject of this paper is a set of 31 air pollution monitoring stations in southern Ontario. Each of these regularly measures a particular subset of ionic sulphate, sulphite, nitrite and ozone. However, this subset varies from station to station. For example only two stations measure all four. Some measure just one. We describe a Bayesian framework for integrating the measurements of these stations to yield a spatial predictive distribution for unmonitored sites and unmeasured concentrations at existing stations. Furthermore we show how this network can be extended by using an entropy maximization criterion. The methods assume that the multivariate response field being measured has a joint Gaussian distribution conditional on its mean and covariance function. A conjugate prior is used for these parameters, some of its hyperparameters being fitted empirically.