Bias‐reduced marginal Akaike information criteria based on a Monte Carlo method for linear mixed‐effects models

In linear mixed‐effects (LME) models, if a fitted model has more random‐effect terms than the true model, a regularity condition required in the asymptotic theory may not hold. In such cases, the marginal Akaike information criterion (AIC) is positively biased for (?2) times the expected log‐likelihood. The asymptotic bias of the maximum log‐likelihood as an estimator of the expected log‐likelihood is evaluated for LME models with balanced design in the context of parameter‐constrained models. Moreover, bias‐reduced marginal AICs for LME models based on a Monte Carlo method are proposed. The performance of the proposed criteria is compared with existing criteria by using example data and by a simulation study. It was found that the bias of the proposed criteria was smaller than that of the existing marginal AIC when a larger model was fitted and that the probability of choosing a smaller model incorrectly was decreased.     

A new large sample goodness of fit test for multivariate normality based on chi squared probability plots

Based on a chi square transform of the multivariate normal data set, we proposed a technique for testing multinormality which is the sum of interpoint squared distances between an ordered set of the transformed observations and the set of the population pth quantiles of the chi squared distribution. The critical values of the test were evaluated for different sample sizes and random vector dimensions through extensive simulations. The empirical type-I-error rates and powers of the proposed test were compared with those of some other well known tests for MVN with the proposed test showing excellent results at large sample sizes.     

城市化水平愈高会愈减少歧视吗?——中国城市居民与外来务工人员之间的社会距离

文章通过对2005年全国综合社会调查数据分析,发现随着一个城市城市化水平的增加,城市居民对居住在这个城市的外来务工人员的歧视态度也愈加严重;沿海地区城市居民比内陆地区城市居民对外来务工人员的歧视度要高。     

网络文化背景下教育特性的全新思考

网络文化与教育是双向互动的关系,网络文化背景下的教育应具有广泛性和平等性、科学性和人文性、个性化和创新性、终身性和全息性、国际性和民族性。     

论摄影意象美的意蕴与构建

意象是中国古典美学的一个概念,是造型艺术超越机械写实囹圄的表达空间,是艺术家心中的风景与气象。摄影意象的提出旨在实现对摄影机械写实属性的超越,本文追溯了摄影意象的渊源,并对摄影意象美的意蕴作了阐释,进而提出了摄影意象美的构建前提与手法,旨在为摄影赢得意象表现自由做前沿性的探索。     

Classification of form under heterogeneity and non-isotropic errors

A number of areas related to learning under supervision have not been fully investigated, particularly the possibility of incorporating the method of classification into shape analysis. In this regard, practical ideas conducive to the improvement of form classification are the focus of interest. Our proposal is to employ a hybrid classifier built on Euclidean Distance Matrix Analysis (EDMA) and Procrustes distance, rather than generalised Procrustes analysis (GPA). In empirical terms, it has been demonstrated that there is notable difference between the estimated form and the true form when EDMA is used as the basis for computation. However, this does not seem to be the case when GPA is employed. With the assumption that no association exists between landmarks, EDMA and GPA are used to calculate the mean form and diagonal weighting matrix to build superimposing classifiers. As our findings indicate, with the use of EDMA estimators, the superimposing classifiers we propose work extremely well, as opposed to the use of GPA, as far as both simulated and real datasets are concerned.     

The evaluation of socio-economic development of development agency regions in Turkey using classical and robust principal component analyses

In this study, classical and robust principal component analyses are used to evaluate socioeconomic development of regions of development agencies that give service on the purpose of decreasing development difference among regions in Turkey. Due to the high differences between development levels of regions outlier problem occurs, hence robust statistical methods are used. Also, classical and robust statistical methods are used to investigate if there are any outliers in data set. In classic principal component analyse, the number of observations must be larger than the number of variables. Otherwise determinant of covariance matrix is zero. In Robust method for Principal Component Analysis (ROBPCA), a robust approach to principal component analyse in high-dimensional data, even if the number of variables is larger than the number of observations, principal components are obtained. In this paper, firstly 26 development agencies are evaluated with 19 variables by using principal component analysis based on classical and robust scatter matrices and then these 26 development agencies are evaluated with 46 variables by using the ROBPCA method.     

距离的矛盾——论梁启超文论的过渡时代性质

梁启超作为一个处于巨变之中的过渡时代的人物,体现了过渡时代错综复杂的思想形态。一方面梁氏的思想显现出了过渡时代的杂乱、未成形和多变的特点;另一方面也显现出其思想未定于一尊时所表现出的多向度探索的思考。梁启超的矛盾思想和时代过渡性质反映在其文论和创作实践上主要表现为:其政治家身份和创作的距离;其创作思想和创作实践的距离;其文学观及创作和读者理解的距离。     

Micro-structure in micro-neighborhoods: A new social distance measure,and its effect on individual and aggregated perceptions of crime and disorder

This study links social network methodology with the social disorganization literature to test the effect of block-level social distance on neighborhood perceived crime and disorder. Employing a unique study design that allows creating matrices of social distance (based on demographic characteristics) between 11 residents on each of over 650 blocks at three time points, we find that more socially distant residents perceive more disorder than their neighbors. Consistent with the bridging social capital literature, overall social distance in the block has a curvilinear relationship with perceived crime. And blocks with two cohesive subgroups, based on social distance, have lower levels of perceived disorder.