印度对华化工产品反倾销的贸易效应分析

随着印度对华化工产品反倾销的频发,其所产生的贸易效应越发值得关注。通过构建半对数线性回归方程,以10位编码的化工行业涉案产品的月度数据作为基础进行实证检验,考察不同阶段贸易破坏效应和贸易转移效应的存在性及其大小,指出印度对华化工产品采取反倾销措施不仅会对我国产生负的贸易破坏效应,同时会引起竞争国对印出口增加,存在正的贸易转移效应。然而对于不同产品,破坏效应出现的时间和大小是有区别的,贸易转移效应则并非普遍存在。     

Regression Methods for Combining Multiple Classifiers

As no single classification method outperforms other classification methods under all circumstances, decision-makers may solve a classification problem using several classification methods and examine their performance for classification purposes in the learning set. Based on this performance, better classification methods might be adopted and poor methods might be avoided. However, which single classification method is the best to predict the classification of new observations is still not clear, especially when some methods offer similar classification performance in the learning set. In this article we present various regression and classical methods, which combine several classification methods to predict the classification of new observations. The quality of the combined classifiers is examined on some real data. Nonparametric regression is the best method of combining classifiers.     

Adaptive Warped Kernel Estimators

In this work, we develop a method of adaptive non‐parametric estimation, based on ‘warped’ kernels. The aim is to estimate a real‐valued function s from a sample of random couples (X,Y). We deal with transformed data (Φ(X),Y), with Φ a one‐to‐one function, to build a collection of kernel estimators. The data‐driven bandwidth selection is performed with a method inspired by Goldenshluger and Lepski (Ann. Statist., 39, 2011, 1608). The method permits to handle various problems such as additive and multiplicative regression, conditional density estimation, hazard rate estimation based on randomly right‐censored data, and cumulative distribution function estimation from current‐status data. The interest is threefold. First, the squared‐bias/variance trade‐off is automatically realized. Next, non‐asymptotic risk bounds are derived. Lastly, the estimator is easily computed, thanks to its simple expression: a short simulation study is presented.     

Wavelet Shrinkage with Double Weibull Prior

In this article, we propose a denoising methodology in the wavelet domain based on a Bayesian hierarchical model using Double Weibull prior. We propose two estimators, one based on posterior mean (Double Weibull Wavelet Shrinker, DWWS) and the other based on larger posterior mode (DWWS-LPM), and show how to calculate them efficiently. Traditionally, mixture priors have been used for modeling sparse wavelet coefficients. The interesting feature of this article is the use of non-mixture prior. We show that the methodology provides good denoising performance, comparable even to state-of-the-art methods that use mixture priors and empirical Bayes setting of hyperparameters, which is demonstrated by extensive simulations on standardly used test functions. An application to real-word dataset is also considered.     

基于加权案例推理模型族的软件成本SVR组合估算

精确地估算软件成本是软件项目成功开发的一个重要保证,直接影响着软件的风险控制和质量保证.为了更好地解决单一估算模型的不足,提出了集成多案例推理(CBR)模型的软件成本组合估算模型.首先,采用六种距离计算公式刻画新旧项目相似度,构建了六种CBR模型,并运用粒子群算法(PSO)来优化CBR模型族中的属性权重.其次,在CBR模型族的基础上,运用支持向量回归机(SVR)模型将不同CBR模型的估算结果进行集成,提高软件成本估算结果的精度.利用Deshamais数据库对模型有效性进行检验,实证结果表明,在六种CBR模型中Euc-CBR、Min-CBR、Gau-CBR和Mah-CBR模型估算结果没有明显差异,Gre-CBR和Man-CBR模型略优;提出的SVR组合估算模型估算精度明显优于单CBR模型和其他线性组合估算模型,能有效提高软件成本的估算精度.     

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。     

自然地理环境贫困效应实证分析——基于空间贫困理论视角

从空间贫困理论的视角,根据自然地理环境、社会经济发展水平与贫困发生之间的关系,构建面板数据模型,并运用2006-2012年新疆17个边境重点贫困县市的面板数据进行实证分析,探讨自然地理环境的贫困发生效应.回归分析结果表明,自然地理条件对农民收入和农村贫困率有显著影响,政府完善区域经济发展战略和相关政策,可以缓解自然地理环境对贫困效应的影响,农业经济的发展对农村贫困率的减低有显著性影响.     

流动人口的自营性收入不平等与工资性收入不平等

利用2005年全国1％人口抽样调查的子样本数据以及2012年流动人口动态监测调查数据,研究了各可观测因素对自营者和受雇者收入分布的解释能力存在何种差异,及其在2005-2012年间所发生的变化.考虑到就业方式选择的内生性问题,文章首先采用转换回归模型对自营者和受雇者的收入方程进行了估计.在此基础上,进一步根据基于回归分析的分解分析方法,利用Shapley分解过程对自营者收入的Gini系数和受雇者收入的Gini系数分别进行了分解分析.结果显示,对于流动人口而言,收入分配过程中的制度性障碍正在减少.