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.     

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。      

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.     

How long is the queuing for public childcare facilities in Korea? An empirical analysis of Korean households' childcare mode choice with the limited availability of public childcare facilities

This paper empirically investigates Korean households' choice of childcare mode using the Korean Childcare Users Survey (2012). A multivariate logit model with partial observability (hereafter, PO‐logit model) is employed to address the issue of Korean households' demand for public childcare facilities exceeding capacity limits. Our estimation result rejects the hypothesis of no queueing at conventional significance levels to advocate use of the PO‐logit model in explaining Korean households' childcare choices. We decompose choice probabilities of public childcare facilities to estimate the size of queuing. Our results imply that 31.8% of parents preferring public childcare facility are forced to choose other childcare modes due to capacity limit.     

Sparse Approximations of Fractional Matérn Fields

We consider fast lattice approximation methods for a solution of a certain stochastic non‐local pseudodifferential operator equation. This equation defines a Matérn class random field. We approximate the pseudodifferential operator with truncated Taylor expansion, spectral domain error functional minimization and rounding approximations. This allows us to construct Gaussian Markov random field approximations. We construct lattice approximations with finite‐difference methods. We show that the solutions can be constructed with overdetermined systems of stochastic matrix equations with sparse matrices, and we solve the system of equations with a sparse Cholesky decomposition. We consider convergence of the truncated Taylor approximation by studying band‐limited Matérn fields. We consider the convergence of the discrete approximations to the continuous limits. Finally, we study numerically the accuracy of different approximation methods with an interpolation problem.     

Kernel partial correlation: a novel approach to capturing conditional independence in graphical models for noisy data

Graphical models capture the conditional independence structure among random variables via existence of edges among vertices. One way of inferring a graph is to identify zero partial correlation coefficients, which is an effective way of finding conditional independence under a multivariate Gaussian setting. For more general settings, we propose kernel partial correlation which extends partial correlation with a combination of two kernel methods. First, a nonparametric function estimation is employed to remove effects from other variables, and then the dependence between remaining random components is assessed through a nonparametric association measure. The proposed approach is not only flexible but also robust under high levels of noise owing to the robustness of the nonparametric approaches.     

Regression imputation with Q-mode clustering for rounded zero replacement in high-dimensional compositional data

The logratio methodology is not applicable when rounded zeros occur in compositional data. There are many methods to deal with rounded zeros. However, some methods are not suitable for analyzing data sets with high dimensionality. Recently, related methods have been developed, but they cannot balance the calculation time and accuracy. For further improvement, we propose a method based on regression imputation with Q-mode clustering. This method forms the groups of parts and builds partial least squares regression with these groups using centered logratio coordinates. We also prove that using centered logratio coordinates or isometric logratio coordinates in the response of partial least squares regression have the equivalent results for the replacement of rounded zeros. Simulation study and real example are conducted to analyze the performance of the proposed method. The results show that the proposed method can reduce the calculation time in higher dimensions and improve the quality of results.     

Optimal Berry–Esseen bound for parameter estimation of SPDE with small noise

We investigate a rate of convergence on asymptotic normality of the maximum likelihood estimator (MLE) for parameter $\theta$ appearing in parabolic SPDEs of the form

$d{u}^{?}(t,x)=(A_0+\theta A_1)u^{?}(t,x)dt+?dW(t,x),$

where $A_0$ and$A_1$ are partial differential operators, $W$ is a cylindrical Brownian motion (CBM) and $?\downarrow 0$. We find an optimal Berry–Esseen bound for central limit theorem (CLT) of the MLE. It is proved by developing techniques based on combining Malliavin calculus and Stein’s method.