Identification and classification of multiple outliers,high leverage points and influential observations in linear regression

Detection of multiple unusual observations such as outliers, high leverage points and influential observations (IOs) in regression is still a challenging task for statisticians due to the well-known masking and swamping effects. In this paper we introduce a robust influence distance that can identify multiple IOs, and propose a sixfold plotting technique based on the well-known group deletion approach to classify regular observations, outliers, high leverage points and IOs simultaneously in linear regression. Experiments through several well-referred data sets and simulation studies demonstrate that the proposed algorithm performs successfully in the presence of multiple unusual observations and can avoid masking and/or swamping effects.     

An improved binary randomized response model using six decks of cards

This article purposes the estimation of population proportion of a sensitive attribute through randomized response technique. An efficient estimator is suggested using six decks of cards to randomise the response. Many existing models can now be viewed as the special case of the proposed model. The superiority of the proposed procedure is established through numerical calculation of percentage relative efficiency with prominent competitors. The proposed procedure is also studied under stratified random sampling protocol. In addition, it is shown that, the proposed stratified estimator, performs better in term of efficiency than its only existing two deck stratified competitor.     

现代远程教育校外学习中心的学习支持服务工作简

在现代远程教育中，具备完善的校外学习支持服务体系是实现远程教学目标的基础，是否能够建立功能完善的支持服务体系直接影响着远程教育的教学质量。在学习支持服务的教学体系中，校外学习中心的学习支持服务相关工作占据着重要的地位，是其重要的组成部分，要想做好远程教育学习支持服务工作，需要加强管理，规范制度。另外，还需要注重学前支持服务工作，有效整合教学资源，增加服务渠道，提升日常的服务质量，进而提升校外学习中心对学生的支持服务工作水平。     

企业行为与经济增长方式的转变

本文构建了一个企业技术升级的路径选择模型,该模型很好地解释了企业行为在经济增长方式转变中的作用。同时,论证了处于工业化中后期的经济体实现经济增长方式转变的必要性,并分析了增长方式转变的制约因素。企业的技术选择行为决定经济增长方式,企业选择技术进步的方式由产品间技术距离决定,技术距离的临界值大小与成本和价格的变化速度有关。相同的临界值条件下,创新导致的技术进步成功可能性更大。笔者提出了促进创新主导的经济增长方式的转变的相关政策建议。     

Answered Callings,Unanswered Callings,or No Calling: Examining a Nationally Representative Sample

Research suggests that workers with unanswered callings have poorer outcomes than those without callings; however, these studies have used small or homogeneous samples (Berg et al., 2010; Gazica & Spector, 2015). We aimed to replicate this finding using a nationally representative sample of 445 full-time workers. We compared key work and life criterion variables across three groups: individuals with answered callings, unanswered callings, and no calling at all. Results linked answered callings to benefits but, unlike earlier studies, suggested that unanswered callings were no worse than lacking a calling. These findings call into question the narrative that unanswered callings are associated with adverse effects, suggesting that career counselors may be able to facilitate discernment of a calling without having a negative impact on those for whom that calling goes unanswered. Research designed to test causal influences of these dynamics is an important next step for understanding the experiences of individuals with answered callings, unanswered callings, or no calling at all.     

The Rate of Convergence of some Asymptotic Expansions for Distribution Approximations via an Esseen Type Estimate

Some asymptotic expansions not necessarily related to the central limit theorem are studied. We first observe that the smoothing inequality of Esseen implies the proximity, in the Kolmogorov distance sense, of the distributions of the random variables of two random sequences satisfying a sort of general asymptotic relation. We then present several instances of this observation. A first example, partially motivated by the the statistical theory of high precision measurements, is given by a uniform asymptotic approximation to (g(X + μ _n )) _n∈?, where g is some smooth function, X is a random variable and (μ _n ) _n∈? is a sequence going to infinity; a multivariate version is also stated and proved. We finally present a second class of examples given by a randomization of the interesting parameter in some classical asymptotic formulas; namely, a generic Laplace's type integral, randomized by the sequence (μ _n X) _n∈?, X being a Gamma distributed random variable.     

Estimation procedures for grouped data – a comparative study

Interval-censored data are very common in the reliability and lifetime data analysis. This paper investigates the performance of different estimation procedures for a special type of interval-censored data, i.e. grouped data, from three widely used lifetime distributions. The approaches considered here include the maximum likelihood estimation, the minimum distance estimation based on chi-square criterion, the moment estimation based on imputation (IM) method and an ad hoc estimation procedure. Although IM-based techniques are extensively used recently, we show that this method is not always effective. It is found that the ad hoc estimation procedure is equivalent to the minimum distance estimation with another distance metric and more effective in the simulation. The procedures of different approaches are presented and their performances are investigated by Monte Carlo simulation for various combinations of sample sizes and parameter settings. The numerical results provide guidelines to analyse grouped data for practitioners when they need to choose a good estimation approach.     

Sensitivity analysis for variance parameters in Bayesian simplex mixed models for proportional data

In this article, we present a Bayesian modeling for response variables restricted to the interval (0, 1), such as proportions and rates, using the simplex distribution for cases in which data have a longitudinal form, taking random effects into account. In order to investigate the stability of posterior distribution, we study through sensitivity analysis, the effect of three different uniparametric prior distributions for variance parameters of random effect on the final estimation. For this purpose, we consider homogeneous and heterogeneous structures for parameters in location and dispersion submodels. Models and results are illustrated with simulated and real data application.