On second-order improved estimation of a gamma scale parameter

This paper concludes our comprehensive study on point estimation of model parameters of a gamma distribution from a second-order decision theoretic point of view. It should be noted that efficient estimation of gamma model parameters for samples ‘not large’ is a challenging task since the exact sampling distributions of the maximum likelihood estimators and its variants are not known. Estimation of a gamma scale parameter has received less attention from the earlier researchers compared to shape parameter estimation. What we have observed here is that improved estimation of the shape parameter does not necessarily lead to improved scale estimation if a natural moment condition (which is also the maximum likelihood restriction) is satisfied. Therefore, this work deals with the gamma scale parameter estimation as a separate new problem, not as a by-product of the shape parameter estimation, and studies several estimators in terms of second-order risk.     

Improving TAIEX forecasting using fuzzy time series with Box–Cox power transformation

Box–Cox together with our newly proposed transformation were implemented in three different real world empirical problems to alleviate noisy and the volatility effect of them. Consequently, a new domain was constructed. Subsequently, universe of discourse for transformed data was established and an approach for calculating effective length of the intervals was then proposed. Considering the steps above, the initial forecasts were performed using frequently used fuzzy time series (FTS) methods on transformed data. Final forecasts were retrieved from initial forecasted values by proper inverse operation. Comparisons of the results demonstrate that the proposed method produced more accurate forecasts compared with existing FTS on original data.     

Some tests for the power series distibutions in one parameter using the kullback-leibler information measure

The purpose of the article is, in case of one sample, to obtain tests concerning the parameter in the power series distribution in one parameter using Ku11back-Leibier information measure. The class of power series distibutions contains a host of discrete distributions. Ve illustrate the general results obtained in case of the geometric distibution.     

有限理性指导下的过渡性制度构建——社会转型背景下侦查程序完善的整体设想

目前理论界对侦查程序的研究理性化色彩过重，学者们多对不同的刑事诉讼模式进行静态比较，得出何种模式相对优劣的结论，从而进行制度构建。这虽然有利于目标模式的选择，但不利于具有可操作性的制度设计。本文从我国社会转型时期的宏观背景出发，以这一特定时期所存在的对侦查机关完成打击犯罪和保障人权双重使命有重大影响的因素为切入点，进行系统审视，提出有限理性的理念，并以此为指导进行过渡性制度设计。     

A diagnostic statistic for functional-coefficient autoregressive models

In this paper, functional coefficient autoregressive (FAR) models proposed by Chen and Tsay (1993) are considered. We propose a diagnostic statistic for FAR models constructed by comparing between parametric and nonparametric estimators of the functional form of the FAR models. We show asymptotic properties of our statistic mathematically and it can be applied to the estimation of the delay parameter and the specification of the functional form of FAR models.     

A note on approximate confidence limits for the negative binomial model

Four methods of approximating confidence limits for the single negative binomial parameter, P, are outlined and an empirical study is presented. Some remarks on prediction intervals are also included.     

SPECIAL ISSUE： ONLINE LITERATURE IN CHINA： PRESENT SITUATION AND THEORETICAL REFLECTIONS Online Writing in the Course of Discourse Transformation： A Review of Ten Outstanding Online Novels of the Past Decade

中国当代文学阅读层面上的价值认同正在经受前所未有的挑战。特别是新世纪以来，新的写作群体、写作方式不断涌现，使固有的理论批评体系遭到撞击、被撕裂，从而导致理论批评不时出现失语现象。随着网络文学的迅猛发展，非主流文学在阅读与消费环节中的影响日益增强，这就使得上述问题转化成了新的矛盾——互相不能包容的阅读隔膜。十多年来，网络上产生了海量的小说文本，逐渐形成了二十多种类型；本文兼顾时间跨度和创作类型，遴选了十年中不同类型的十部佳作，并针对它们区别于纸质媒体的艺术审美和创作特点进行了述评。     

几种岭参数选择方法的比较

比较了不同的几种岭参数选择方法的应用效果，结果表明，几种方法中没有一种方法被认为是优于其它的方法。但在均方误差准则下．几种岭参数选择方法所获得的估计都改进了设计阵呈病态时的最小二乘估计。     

Identifying Latent Structures in Panel Data

This paper provides a novel mechanism for identifying and estimating latent group structures in panel data using penalized techniques. We consider both linear and nonlinear models where the regression coefficients are heterogeneous across groups but homogeneous within a group and the group membership is unknown. Two approaches are considered—penalized profile likelihood (PPL) estimation for the general nonlinear models without endogenous regressors, and penalized GMM (PGMM) estimation for linear models with endogeneity. In both cases, we develop a new variant of Lasso called classifier‐Lasso (C‐Lasso) that serves to shrink individual coefficients to the unknown group‐specific coefficients. C‐Lasso achieves simultaneous classification and consistent estimation in a single step and the classification exhibits the desirable property of uniform consistency. For PPL estimation, C‐Lasso also achieves the oracle property so that group‐specific parameter estimators are asymptotically equivalent to infeasible estimators that use individual group identity information. For PGMM estimation, the oracle property of C‐Lasso is preserved in some special cases. Simulations demonstrate good finite‐sample performance of the approach in both classification and estimation. Empirical applications to both linear and nonlinear models are presented.     

转型加速时期西部少数民族地区结构性贫困研究述论

文章认为西部少数民族地区在社会转型加快时期的贫困问题基本上是结构性贫困,并对这种结构性贫困问题的具体特征及其产生的社会危害进行纬度结构分析,最后系统地从建构现代国家治理体系和治理现代化的背景下提出了治理路径。