PLS算法的顾客满意度指数模型

通过对国内外顾客满意度指数模型的对比及对我国的现状分析,提出顾客满意度测评的常规模型。在此基础上对常规模型的模型设定、模型估计和模型评价进行研究;利用PLS算法估计模型中的各个参数,将外部估计分为无缺失值和有缺失值两种情况,针对后者提出局部权重新定的缺失值处理方法;以某食品公司为研究对象,对构建的顾客满意度测评常规模型进行实证分析和评价。结果表明:常规模型的显变量符合单一纬度条件、具有一定的解释能力和良好的内敛效度,拟合效果可以接受,测评结果是满意和有效的,为PLS路径模型研究及缺失值处理提供了实用方法。     

次分数布朗运动下带交易费用的备兑权证定价

为了体现金融资产的长记忆性,采用次分数布朗运动刻画备兑权证标的资产价格变化的行为模式。利用随机分析理论和偏微分方程方法,建立了次分数布朗运动下带交易费用的备兑权证定价模型,进一步研究了定价模型的参数估计问题。最后,采用我国权证市场实际数据进行了实证分析,通过比较不同定价模型的结果说明了长记忆性和交易费用对定价结果有着显著的影响。     

Best Nonparametric Bounds on Demand Responses

This paper uses revealed preference inequalities to provide the tightest possible (best) nonparametric bounds on predicted consumer responses to price changes using consumer‐level data over a finite set of relative price changes. These responses are allowed to vary nonparametrically across the income distribution. This is achieved by combining the theory of revealed preference with the semiparametric estimation of consumer expansion paths (Engel curves). We label these expansion path based bounds on demand responses as E‐bounds. Deviations from revealed preference restrictions are measured by preference perturbations which are shown to usefully characterize taste change and to provide a stochastic environment within which violations of revealed preference inequalities can be assessed.     

根本之守与应时之变——鸦片战争后失事官员责任追究透视

鸦片战争结束后,清王朝并无我们期待的深刻反思。他们所进行的善后工作中一项重要的内容是战败责任追究,这包括道德拷问和法律责任追究两方面,这两者是王朝要坚守的根本。但承担责任的地方官员,对一场力量悬殊的中外战争中职守责任的理解与朝廷存在差异,同时他们更关注如何应对战后外部的压力和复杂的局面,要求朝廷能做一些变通。根本之守与应时之变的分歧构成战后政治变动的内在张力,并预示着整个晚清政局的走向。     

中国法语境下的并存债务承担制度

鉴于并存债务承担制度在立法及理论研究上的缺憾,文章对该制度进行系统研究。正确理解并存债务承担制度,必须考虑到我国特定的学术与立法背景。文章分析了并存债务承担制度的内涵与外延,并通过对《合同法》第84条的解释论分析,认为并存债务承担并不包含在“部分移转”之中,我国立法并未承认并存债务承担制度,存在立法漏洞。文章突出债务承担合同的中心地位,并以此为基础讨论并存债务承担中履行障碍的解决机制。      

基于PLS路径模型的顾客满意度测评研究

根据美国顾客满意度指数模型,提出了一种基于PLS路径模型的顾客满意度测评模型;详细阐述了模型设定、模型估计和模型评价。实例证明该顾客满意度测评模型显变量符合单一纬度条件、具有良好的内敛效度、具有一定的解释能力,拟合效果可以接受,为国内顾客满意度测评研究提供了实用方法。     

Parameter Estimation for a Bidimensional Partially Observed Ornstein–Uhlenbeck Process with Biological Application

Abstract. We consider a bidimensional Ornstein–Uhlenbeck process to describe the tissue microvascularization in anti‐cancer therapy. Data are discrete, partial and noisy observations of this stochastic differential equation (SDE). Our aim is to estimate the SDE parameters. We use the main advantage of a one‐dimensional observation to obtain an easy way to compute the exact likelihood using the Kalman filter recursion, which allows to implement an easy numerical maximization of the likelihood. Furthermore, we establish the link between the observations and an ARMA process and we deduce the asymptotic properties of the maximum likelihood estimator. We show that this ARMA property can be generalized to a higher dimensional underlying Ornstein–Uhlenbeck diffusion. We compare this estimator with the one obtained by the well‐known expectation maximization algorithm on simulated data. Our estimation methods can be directly applied to other biological contexts such as drug pharmacokinetics or hormone secretions.     

微分方程的解关于部分变元的弱吸引性

本文提出关于部分变元的弱吸引及其相关概念,并给出判定他们的充分条件。文献[]、[]中的相应结果可作为本文的特例。12     

Nonparametric Identification under Discrete Variation

This paper provides weak conditions under which there is nonparametric interval identification of local features of a structural function that depends on a discrete endogenous variable and is nonseparable in latent variates. The function delivers values of a discrete or continuous outcome and instruments may be discrete valued. Application of the analog principle leads to quantile regression based interval estimators of values and partial differences of structural functions. The results are used to investigate the nonparametric identifying power of the quarter‐of‐birth instruments used in Angrist and Krueger's 1991 study of the returns to schooling.