Local influence in ridge semiparametric models

ABSTRACT

Ridge penalized least-squares estimators has been suggested as an alternative to the minimum penalized sum of squares estimates in the presence of collinearity among the explanatory variables in semiparametric regression models (SPRMs). This paper studies the local influence of minor perturbations on the ridge estimates in the SPRM. The diagnostics under the perturbation of ridge penalized sum of squares, response variable, explanatory variables and ridge parameter are considered. Some local influence diagnostics are given. A Monte Carlo simulation study and a real example are used to illustrate the proposed perturbations.     

The empirical analysis of the -bilateral optimized combinatorial auction model

This study proposes a new and highly efficient dynamic combinatorial auction mechanism—the N-bilateral optimized combinatorial auction (N-BOCA). N-BOCA is a flexible iterative combinatorial auction model that offers more optimized trading for multiple suppliers and purchasers in the supply chain than one-sided combinatorial auction. We design the N-BOCA model from the perspectives of market architecture, trading rules, and decision strategy for winner determination, the decision strategy for winner determination needs flexible optimization modeling capability. Thus rule-based reasoning was applied for reflecting the flexible decision strategies. We also show the viability of N-BOCA through Paired Samples T-test experimentation. It shows that N-BOCA yields higher purchase efficiency and effectiveness than the one-auctioneer to multi-bidders (1-to-N) combinatorial auction mechanism.     

Polynomial Spline Estimation for a Generalized Additive Coefficient Model

Abstract.  We study a semiparametric generalized additive coefficient model (GACM), in which linear predictors in the conventional generalized linear models are generalized to unknown functions depending on certain covariates, and approximate the non-parametric functions by using polynomial spline. The asymptotic expansion with optimal rates of convergence for the estimators of the non-parametric part is established. Semiparametric generalized likelihood ratio test is also proposed to check if a non-parametric coefficient can be simplified as a parametric one. A conditional bootstrap version is suggested to approximate the distribution of the test under the null hypothesis. Extensive Monte Carlo simulation studies are conducted to examine the finite sample performance of the proposed methods. We further apply the proposed model and methods to a data set from a human visceral Leishmaniasis study conducted in Brazil from 1994 to 1997. Numerical results outperform the traditional generalized linear model and the proposed GACM is preferable.     

On Variance Components in Semiparametric Mixed Models for Longitudinal Data

Abstract. First, to test the existence of random effects in semiparametric mixed models (SMMs) under only moment conditions on random effects and errors, we propose a very simple and easily implemented non‐parametric test based on a difference between two estimators of the error variance. One test is consistent only under the null and the other can be so under both the null and alternatives. Instead of erroneously solving the non‐standard two‐sided testing problem, as in most papers in the literature, we solve it correctly and prove that the asymptotic distribution of our test statistic is standard normal. This avoids Monte Carlo approximations to obtain p ‐values, as is needed for many existing methods, and the test can detect local alternatives approaching the null at rates up to root n. Second, as the higher moments of the error are necessarily estimated because the standardizing constant involves these quantities, we propose a general method to conveniently estimate any moments of the error. Finally, a simulation study and a real data analysis are conducted to investigate the properties of our procedures.     

人事信息管理系统（网站）的设计与开发

本系统采用ASP技术作为前台开发工具,Access作为后台数据库的基于B/S平台的两层模式管理系统.旨在实现对现有的煤矿企业人事管理工作中遇到的各种情况和大量数据进行数据库存储,设计并完成对其各种数据的分类、查询和统计,在深入研究的过程中,尽可能实现各类方便友好的操作界面和数据报表.     

B2C电子商务中基于D-S证据融合理论的推荐信任评价模型

B2C电子商务中成熟消费者推荐是增强新消费者信任的重要渠道.基于证据融合理论,提出一种B2C电子商务中的推荐信任评价模型,从消费者、商品、服务商及其网站、技术和人文环境等方面多视角地分析B2C电子商务中的在线感知信任影响因素,由在线感知信任影响因素建立成熟消费者的个体信任评价指标;对于一个新消费者,根据他熟悉的多个成熟消费者的个体信任评价,基于D-S证据融合理论,提出由多个成熟消费者的信任评价融合而成的推荐信任评价模型,将提出的推荐信任评价模型应用于实际B2C在线购物推荐信任评价.实验结果表明,该模型可以有效地描述新消费者的推荐信任评价过程.     

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.     

基于Airbnb网络文本数据的旅游者民宿体验感知研究

民宿作为分享经济在旅游领域发展的新业态,为旅游者提供了一种全新的休闲方式。为了深入剖析影响旅游者民宿体验感知的关键因素,利用网络爬虫技术采集Airbnb用户评论数据作为研究样本,依循扎根理论方法的开放式编码、主轴式编码及选择式编码的三重过程,构建了旅游者民宿体验感知模型;借助ROST CM6.0软件从旅游者的正面评价及负面评价中提取高频特征词,分别对旅游者积极感知和消极感知的影响因素进行分析,并将城市民宿与乡村民宿进行比较。结果表明:旅游者对民宿体验的感知贯穿于旅游前期待体验—旅游中感受体验—旅游回味体验这3个阶段,由体验期望、体验前准备、民宿周围环境、民宿核心场景体验、体验后评价等5个维度构成;旅游者对城市民宿及乡村民宿的积极感知因素具有一致性,主要表现在地理位置、自然环境、文化环境、民宿特色和主客互动等方面;而消极感知因素具有差异性,配套设施和卫生条件是旅游者对城市民宿体验消极感知的主要影响因素,旅游者对乡村民宿的消极感知受到地理位置、基础设施及配套设施等多种因素的影响。     

Coverage Properties of Confidence Intervals for Generalized Additive Model Components

Abstract. We study the coverage properties of Bayesian confidence intervals for the smooth component functions of generalized additive models (GAMs) represented using any penalized regression spline approach. The intervals are the usual generalization of the intervals first proposed by Wahba and Silverman in 1983 and 1985, respectively, to the GAM component context. We present simulation evidence showing these intervals have close to nominal ‘across‐the‐function’ frequentist coverage probabilities, except when the truth is close to a straight line/plane function. We extend the argument introduced by Nychka in 1988 for univariate smoothing splines to explain these results. The theoretical argument suggests that close to nominal coverage probabilities can be achieved, provided that heavy oversmoothing is avoided, so that the bias is not too large a proportion of the sampling variability. The theoretical results allow us to derive alternative intervals from a purely frequentist point of view, and to explain the impact that the neglect of smoothing parameter variability has on confidence interval performance. They also suggest switching the target of inference for component‐wise intervals away from smooth components in the space of the GAM identifiability constraints.     

B2C网站设计因素与初始信任关系的实证研究

通过实证探索并验证了网站结构、网站内容和视觉效果对消费者初始信任的影响,同时还验证了社会存在感在其中所起的中介作用.研究结果发现:网站结构和网站内容对消费者初始信任有着直接的积极影响,社会存在感在其中承担着部分中介作用;网站视觉效果对消费者初始信任的影响虽不显著,但却对社会存在感有着显著的影响.