A characteristic function approach to the biased sampling model,with application to robust logistic regression

Many sampling problems from multiple populations can be considered under the semiparametric framework of the biased, or weighted, sampling model. Included under this framework is logistic regression under case–control sampling. For any model, atypical observations can greatly influence the maximum likelihood estimate of the parameters. Several robust alternatives have been proposed for the special case of logistic regression. However, some current techniques can exhibit poor behavior in many common situations. In this paper a new family of procedures are constructed to estimate the parameters in the semiparametric biased sampling model. The procedures incorporate a minimum distance approach, but are instead based on characteristic functions. The estimators can also be represented as the minimizers of quadratic forms in simple residuals, thus yielding straightforward computation. For the case of logistic regression, the resulting estimators are shown to be competitive with the existing robust approaches in terms of both robustness and efficiency, while maintaining affine equivariance. The approach is developed under the case–control sampling scheme, yet is shown to be applicable under prospective sampling logistic regression as well.     

Comment on An and Schorfheide's Bayesian Analysis of DSGE Models

An and Schorfheide's article provides an excellent review of Bayesian estimation of DSGE models. Rather than recapitulating the points already made in this article, my comment focuses on three aspects. It proposes a convergence measure to take account of serial correlation of MCMC draws, explains why the DSGE-VAR framework for policy analysis can be improved by avoiding the ad hoc identification assumption, and discusses an alternative structural approach to model misspecification.     

文化差异、地理距离对我国各省分国别(地区）出口贸易的影响——基于空间面板数据的实证研究

利用2001-2009年中国30个省分分国别（地区）的出口贸易数据,采用空间探索性数据分析方法分析了各国及地区在我国的出口贸易空间格局,发现各国（地区）在我国的出口贸易中表现出较为显著的空间相关性。进一步,本文构建了考虑空间滞后因子的引力模型实证分析了文化差异和运输距离对我国各省分国别（地区）出口贸易的影响。研究结果表明：我国邻省出口对本省的空间溢出效应随着时间的推移不断增强;而邻省与本省在出口伙伴国选择上的“竞争效应”并不明显;文化差异在各国及地区在我国各省的出口贸易中所起的限制性作用表现突出;而陆运距离对各省分国别（地区）出口贸易的负向影响要明显大于海运距离,且随着时间的推移有不断扩大的迹象。     

心理期望：政治认同生成的内隐机制

政治认同是公民对国家政治诸要素所产生的一种心理上的归属感。心理期望作为政治认同的内隐机制,从需要因素看,可分为自发性政治认同需要和引致性政治认同需要。而对需要的满足,则取决于主体的自我政治期望和社会政治期望的契合程度及运行路向。现实问题往往因对期望的认知错位而产生各异的政治认同距离进而给个体和政府等带来心理压力。如何把这种压力保持在一定的安全阈值范围内而使政府和个人在期望心理供求方面处于大体均衡,成为优化政治认同效果的现实选择。     

基于单位球面生成的等距双NURBS刀具路径规划

目前由离散刀位点数据生成的2条NURBS曲线刀具路径中,刀轴点NURBS曲线与刀具中心点NURBS曲线间 距有可能存在不相等的问题,提出一种单位球面下优化刀轴矢量NURBS曲线的方法,用以解决生成的等距双NURBS刀 具路径中2条NURBS曲线间距有可能不相等的问题。算例表明,本算法可以对工件坐标系下的线性刀路进行光顺,确 保双NURBS样条曲线的间距相等。     

秩估计及向量广义线性模型在风险投资中应用

从风险投资案例中整理发现内在变化规律,有助于把握投资方向和路径。以2001—2011年全球投资公司每轮平均投资数据为例,由于数据不具备正态性和方差齐次性,基于秩估计方差分析,结果表明,各年之间均值存在显著差异。假设平均投资服从伽玛分布,其形状参数和尺度参数是年份的二次函数,基于向量广义线性模型估计各参数。最后预测2015年伽玛分布形状参数为1．1959,尺度参数为5816．186。风险投资位于任何区间的概率都可以通过分布函数计算。     

Profit-oriented productivity change

This study develops an applicable profit-oriented productivity indicator when producers pursue profit maximization and can recognize input and output prices. We define the indicator, inspired by the Luenberger indicator and the Nerlovian efficiency measurement, in terms of both quantity distance functions and profit. Hence, the study׳s first stage decomposes the profit-oriented productivity change into two terms: profit efficiency change and profit technology change. Second, we decompose profit efficiency change into the changes in technical efficiency and allocative efficiency. Finally, profit technology change is separated into two components for capturing the shifts of technology and relative output/input prices. These decompositions provide a more complete picture of the sources of productivity change. We illustrate them with a sample of Taiwanese banks and compute the results using the models of directional distance functions.     

The two-dimensional vector packing problem with piecewise linear cost function

The two-dimensional vector packing problem with piecewise linear cost function (2DVPP-PLC) is a practical problem faced by a manufacturer of children׳s apparel that ships products using courier service. The manufacturer must ship a number of items using standard-sized cartons, where the cost of a carton quoted by the courier is determined by a piecewise linear function of its weight. The cost function is not necessarily convex or concave. The objective is to pack all given items into a set of cartons such that the total delivery cost is minimized while observing both the weight limit and volume capacity constraints. This problem is commonly faced by many manufacturers that ship products using courier service. We formulate the problem as an integer programming model. Since the 2DVPP-PLC generalizes the classical bin packing problem, it is more complex and challenging. Solving it directly using CPLEX is successful only for small instances. We propose a simple heuristic that is extremely fast and produces high-quality solutions for instances of practical size. We develop an iterative local search algorithm to improve the solution quality further. We generate two categories of test data that can serve as benchmark for future research.     

Managing stochastic demand in an Inventory Routing Problem with transportation procurement

We study an Inventory Routing Problem in which the supplier has a limited production capacity and the stochastic demand of the retailers is satisfied with procurement of transportation services. The aim is to minimize the total expected cost over a planning horizon, given by the sum of the inventory cost at the supplier, the inventory cost at the retailers, the penalty cost for stock-out at the retailers and the transportation cost. First, we show that a policy based just on the average demand can have a total expected cost infinitely worse than the one obtained by taking into account the overall probability distribution of the demand in the decision process. Therefore, we introduce a stochastic dynamic programming formulation of the problem that allows us to find an optimal policy in small size instances. Finally, we design and implement a matheuristic approach, integrating a rollout algorithm and an optimal solution of mixed-integer linear programming models, which is able to solve realistic size problem instances. Computational results allow us to provide managerial insights concerning the management of stochastic demand.     

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.