专业化交易组织成长与区域经济发展--再论农村市场经济发展的"义乌模式"

义乌区域经济发展的动因不是工业化,而是市场化;商人的集体行动与政府的开明决策,使义乌成为全国最大的小商品流通中心;"义乌模式"的优势,在于交易方式的专业化,小商品市场的专业化交易形成了信息规模经济、外部规模经济和范围经济,从而确立了义乌小商品的低成本优势;尔后,市场秩序扩展、专业化交换组织成长与产业集聚发展的良性互动,形成了义乌独特的工业化、城市化路径.     

略论闽语研究的“西进”

闽语通行地域跨越多个省份及海外华人社区,人口大约不会少于7000万人。闽语研究历史悠久,成果丰硕。研究面日益扩大,研究内容日益深化。然而,以往的闽语研究,仍存在着研究布局不够平衡的问题。研究的范围多集中在闽南、闽东这两支上,以福建的厦、漳、泉闽南话及粤东属闽南方言系统的潮汕话,和以福州话为代表的闽东闽语成果较为可观。而相对忽略了对边远的、分散的闽语方言点的调查。为此,文章认为闽语研究应尽可能扩大调查的覆盖面,提出多把眼光射向那些分布在闽语大本营闽、台以西的海南岛、粤西南以及广西境内的闽语通行地区,是为“西进”。     

西方国家意识形态扩张的现代性路径及应对方略

生态、潮流、反恐、普世等问题已异化为西方意识形态扩张的现代性路径;从全球化趋势的形成和发展、主流意识形态建设的弱化、新媒体发展和普及等方面着力分析西方意识形态扩张现代性路径的诸多原因,加强马克思主义意识形态宣传教育、提升马克思主义意识形态交往的主动权和影响力、促进社会发展和惠民建设等进行应对。     

品牌拓展新市场过程中消费者选择行为研究

研究消费者品牌选择行为是进行品牌拓展新市场的前提。本文基于消费者决策理论,利用元胞自动机分析了品牌文化、广告宣传、邻居关系及数量、竞争者、市场的经济环境等对消费者进行品牌选择时的影响,研究结果表明该模型能较好地模拟出品牌进行拓展新市场过程中的消费者选择行为。通过对品牌拓展新市场过程中的消费者选择行为的分析,找出更适合进行品牌扩张的区域。     

Improving variance function estimation in semiparametric longitudinal data analysis

We propose an efficient and robust method for variance function estimation in semiparametric longitudinal data analysis. The method utilizes a local log‐linear approximation for the variance function and adopts a generalized estimating equation approach to account for within subject correlations. We show theoretically and empirically that our method outperforms estimators using working independence that ignores the correlations. The Canadian Journal of Statistics 39: 656–670; 2011. © 2011 Statistical Society of Canada     

Classical testing in functional linear models

We extend four tests common in classical regression – Wald, score, likelihood ratio and F tests – to functional linear regression, for testing the null hypothesis, that there is no association between a scalar response and a functional covariate. Using functional principal component analysis, we re-express the functional linear model as a standard linear model, where the effect of the functional covariate can be approximated by a finite linear combination of the functional principal component scores. In this setting, we consider application of the four traditional tests. The proposed testing procedures are investigated theoretically for densely observed functional covariates when the number of principal components diverges. Using the theoretical distribution of the tests under the alternative hypothesis, we develop a procedure for sample size calculation in the context of functional linear regression. The four tests are further compared numerically for both densely and sparsely observed noisy functional data in simulation experiments and using two real data applications.     

Asymptotic distribution of regression correlation coefficient for Poisson regression model

This study treats an asymptotic distribution for measures of predictive power for generalized linear models (GLMs). We focus on the regression correlation coefficient (RCC) that is one of the measures of predictive power. The RCC, proposed by Zheng and Agresti is a population value and a generalization of the population value for the coefficient of determination. Therefore, the RCC is easy to interpret and familiar. Recently, Takahashi and Kurosawa provided an explicit form of the RCC and proposed a new RCC estimator for a Poisson regression model. They also showed the validity of the new estimator compared with other estimators. This study discusses the new statistical properties of the RCC for the Poisson regression model. Furthermore, we show an asymptotic normality of the RCC estimator.     

A Bayesian approach to non-parametric monotone function estimation

Summary.  The paper proposes two Bayesian approaches to non-parametric monotone function estimation. The first approach uses a hierarchical Bayes framework and a characterization of smooth monotone functions given by Ramsay that allows unconstrained estimation. The second approach uses a Bayesian regression spline model of Smith and Kohn with a mixture distribution of constrained normal distributions as the prior for the regression coefficients to ensure the monotonicity of the resulting function estimate. The small sample properties of the two function estimators across a range of functions are provided via simulation and compared with existing methods. Asymptotic results are also given that show that Bayesian methods provide consistent function estimators for a large class of smooth functions. An example is provided involving economic demand functions that illustrates the application of the constrained regression spline estimator in the context of a multiple-regression model where two functions are constrained to be monotone.     

BARTLETT CORRECTED LIKELIHOOD RATIO TESTS IN LOCATION-SCALE NONLINEAR MODELS

The paper derives Bartlett corrections for improving the chisquare approximation to the likelihood ratio statistics in a class of location-scale family of distributions, which encompasses the elliptical family of distributions and also asymmetric distributions such as the extreme value distributions. We present, in matrix notation, a Bartlett corrected likelihood ratio statistic for testing that a subset of the nonlinear regression coefficients in this class of models equals a given vector of constants. The formulae derived are simple enough to be used analytically to obtain several Bartlett corrections in a variety of important models. We show that these formulae generalize a number of previously published results. We also present simulation results comparing the sizes and powers of the usual likelihood ratio tests and their Bartlett corrected versions when the scale parameter is considered known and when this parameter is uncorrectly specified.     

A simple approximation for the doubly noncentral t-distribution

A simple approximation for the doubly noncentral t-distribution, based upon the Fieller-Geary Theorem (1930) and approximate normality of the square root of the noncentral chi-square variable observed by Patnaik (1949), is developed, This approximation and an Edgeworth series expansion associated with it are evaluated. The simple approximation is seen to be reasonably accurate for most practical purposes.