城市供水企业客户满意度的实证研究

本文根据对重庆市主城区供水企业客户满意度的问卷调查,先运用因子分析法探索影响供水企业客户满要素,再通过构建客户满意的结构方程模型(Structural Equation Modeling,简称为SEM)验证关键要素与客户满意度的相关性和相关程度.最后根据分析结果提出供水企业提高客户满意度的策略建议.     

公司治理与资本结构对上市公司价值创造能力综合影响的实证研究

董事会特征、股权结构、资本结构、公司财务、公司价值等都是不可直接观测的潜变量,为定量研究其内在关系带来了挑战。本文在分析公司治理与资本结构对上市公司价值创造能力影响机理的基础上构建结构方程模型,通过因子分析对潜变量进行计量,通过路径分析讨论潜变量之间的依赖关系,并建立上市公司价值创造能力影响因素的综合分析框架,从整体上评估董事会特征、股权结构、资本结构、公司财务等因素对上市公司价值创造能力的直接和间接影响效果。结果表明:董事会特征与股权结构对上市公司价值创造能力的直接影响都不显著,只是存在间接影响;资本结构既存在直接影响,也存在间接影响;公司财务存在直接影响;进一步,按照对上市公司价值创造能力总体影响程度大小依次排序为:资本结构、股权结构、公司财务、董事会特征。     

Verallgemeinerte bayes-verfahren bei sequentiellen testproblemen

In this paper, problems of sequential decision theory are taken into consideration by extending the definition of the BAYES rule and treating BAYES rules. This generalisation is quite useful for practice. In many cases only BAYES rules can be calculated. The conditions under which such sequential decision procedures exist are demonstrated, as well as how to construct them on a scheme of backward induction resulting in the conclusion that the existence of BAYES rules needs essentially weaker assumptions than the existence of BAYES rules.Futhermore, methods are searched to simplify the construction of optimal stopping rules. Some illustrative examples are given.     

Variable selection and estimation for multivariate panel count data via the seamless‐${\it L}_{{\rm 0}}$ penalty

This paper considers regression analysis of multivariate panel count data with the focus on variable selection and estimation of significant covariate effects. For the problem, we adopt the penalized estimating equation approach with a focus on the use of the seamless‐$L_0$ penalty. The proposed approach selects variables and estimates regression coefficients simultaneously and the asymptotic properties of the resulting estimates are established. The procedure can be easily carried out with the Newton–Raphson algorithm and is evaluated by simulation studies. Also it is applied to a motivating data set arising from a skin cancer study. The Canadian Journal of Statistics 41: 368–385; 2013 © 2013 Statistical Society of Canada     

Test-Based Interval Estimation Under the Accelerated Failure Time Model

Some new results of a distance—based (DB) model for prediction with mixed variables are presented and discussed. This model can be thought of as a linear model where predictor variables for a response Y are obtained from the observed ones via classic multidimensional scaling. A coefficient is introduced in order to choose the most predictive dimensions, providing a solution to the problem of small variances and a very large number n of observations (the dimensionality increases as n). The problem of missing data is explored and a DB solution is proposed. It is shown that this approach can be regarded as a kind of ridge regression when the usual Euclidean distance is used.     

A Comparison Between Two Multivariate EWMA Schemes

The signal issued by a control chart triggers the process professionals to investigate the special cause. Change point methods simplify the efforts to search for and identify the special cause. In this study, using maximum likelihood estimation, a multivariate joint change point estimation procedure for monitoring both location and dispersion simultaneously is proposed. After a signal is generated by the simultaneously used Hotelling's T ² and/or generalized variance control charts, the procedure starts detecting the time of the change. The performance of the proposed method for several structural changes for the mean vector and covariance matrix is discussed.     

Some Properties of the Pivotal Statistic Based on the Asymptotically Distribution-Free Theory in Structural Equation Modeling

For normally distributed data, the asymptotic bias and skewness of the pivotal statistic Studentized by the asymptotically distribution-free standard error are shown to be the same as those given by the normal theory in structural equation modeling. This gives the same asymptotic null distributions of the two pivotal statistics up to the next order beyond the usual normal approximation under normality. With an alternative hypothesis, the asymptotic variances of the two statistics under normality/non normality are also derived. It is, however, shown that the asymptotic variances of the non null distributions of the statistics are generally different even under normality.     

A note on simultaneous inference with rerandomization tests

Valid simultaneous confidence intervals based on rerandomization are provided for the first time. They are derived from joint confidence regions which are constructed by testing for all possible parametric values. A simple exampe illustrates these confidence intervals and compares inferences from them with other methods.