Penalized inverse probability weighted estimators for weighted rank regression with missing covariates

Abstract

In this article, we study the variable selection and estimation for linear regression models with missing covariates. The proposed estimation method is almost as efficient as the popular least-squares-based estimation method for normal random errors and empirically shown to be much more efficient and robust with respect to heavy tailed errors or outliers in the responses and covariates. To achieve sparsity, a variable selection procedure based on SCAD is proposed to conduct estimation and variable selection simultaneously. The procedure is shown to possess the oracle property. To deal with the covariates missing, we consider the inverse probability weighted estimators for the linear model when the selection probability is known or unknown. It is shown that the estimator by using estimated selection probability has a smaller asymptotic variance than that with true selection probability, thus is more efficient. Therefore, the important Horvitz-Thompson property is verified for penalized rank estimator with the covariates missing in the linear model. Some numerical examples are provided to demonstrate the performance of the estimators.     

Approximate Bayesian Computation for Exponential Random Graph Models for Large Social Networks

We consider the issue of sampling from the posterior distribution of exponential random graph (ERG) models and other statistical models with intractable normalizing constants. Existing methods based on exact sampling are either infeasible or require very long computing time. We study a class of approximate Markov chain Monte Carlo (MCMC) sampling schemes that deal with this issue. We also develop a new Metropolis–Hastings kernel to sample sparse large networks from ERG models. We illustrate the proposed methods on several examples.     

Semiparametric Smooth Coefficient Stochastic Frontier Model With Panel Data

ABSTRACT

We investigate the semiparametric smooth coefficient stochastic frontier model for panel data in which the distribution of the composite error term is assumed to be of known form but depends on some environmental variables. We propose multi-step estimators for the smooth coefficient functions as well as the parameters of the distribution of the composite error term and obtain their asymptotic properties. The Monte Carlo study demonstrates that the proposed estimators perform well in finite samples. We also consider an application and perform model specification test, construct confidence intervals, and estimate efficiency scores that depend on some environmental variables. The application uses a panel data on 451 large U.S. firms to explore the effects of computerization on productivity. Results show that two popular parametric models used in the stochastic frontier literature are likely to be misspecified. Compared with the parametric estimates, our semiparametric model shows a positive and larger overall effect of computer capital on the productivity. The efficiency levels, however, were not much different among the models. Supplementary materials for this article are available online.     

Performance analysis of the retrial queues with finite number of sources and service interruptions

This paper aims at presenting an analytic approach for investigating a single-server retrial queue with finite population of customers where the server is subject to interruptions. A free source may generate a primary call to request service. If the server is free upon arrival, the call starts to be served and the service times are independent, generally distributed random variables. During the service time the source cannot generate a new primary call. After service the source moves into the free state and can generate a new primary call. There is no waiting space in front of the server, and a call who finds the server unavailable upon arrival joins an orbit of unsatisfied customers. The server is subject to interruptions during the service processes. When the server is interrupted, the call being served just before server interruption goes to the retrial orbit and will retry its luck after a random amount of time until it finds the server available. The recovery times of the interrupted server are assumed to be generally distributed. Our analysis extends previous work on this topic and includes the analysis of the arriving customer’s distribution, the busy period, and the waiting time process.     

“国家与地方社会”关系中的宗族研究范式及其存在的问题

人类学与社会史的汉人宗族研究之主流,实际上一直放在“国家与地方社会”关系的框架内来展开的,以致形成了一种思维范式.这个范式的主要特点是把宗族当成国家与地方社会交流的平台.传统帝国时期,国家支持宗族的存在,以维持地方社会秩序,支撑帝国的整体运转;但现代化运动却要试图革除之,因为它阻碍了现代社会的建立.在某种意义上说,这个视角也的确合乎中国的历史实情,因而今后需要继续加以开拓和深化.但必须意识到,它也遮蔽了作为亲属制度意义上的宗族之文化内涵.也就说,宗族不仅是政治的、经济的,更主要是文化的、风俗的.回归文化的角度理解宗族,是今后超越“国家与地方社会”关系中的宗族范式的一条可尝试的路径.     

试析少数民族贫困大学生资助体系及完善策略——以青海师范大学为例

目前高校贫困生资助工作受到国家和社会的广泛关注,各高校建立了“奖、贷、助、补、免”为主的贫困大学生资助体系,但未能考虑少数民族贫困大学生的特殊情况,仍然不能从根本上解决这一群体的资助问题.通过对当前少数民族学生资助现状分析和现行少数民族学生资助体系的论析,从区域等级化、资助形式、思想教育和辅导员队伍建设等方面提出优化少数民族贫困学生资助工作的策略.     

关于将藏中南地区大开发大开放纳入国家重点开发战略的建议

藏中南地区即西藏“一江三河”是国家西部大开发战略与《全国主体功能区》规划的重点开发区,目前启动大开发大开放不仅是因为其有良好的区位条件,而且具有经济开发的资源条件和环境支撑条件.经过多年的发展,藏中南地区有较好的开发基础,为进一步开发打下了坚实的基础.此外,新疆等边疆少数民族地区重点区域开发实践为藏中南提供了有益的启示.为此,建议启动藏中南地区大开发大开放并加紧列入党和政府的议事日程,加快制定藏中南重点开发区发展规划,明确藏中南重点开发区的发展方向,中央制定藏中南重点开发区的特殊政策.     

北宋书序作者所选择的传播因素分析

书序具有重要的传播作用,以北宋诗文集序为对象考察,书序作者在选择推动传播的因素时,对作品艺术性、知识性等文本因素的关注不如对作家身份、生平轶事等非文本因素普遍。其中原因,从书序作者的操作层面来看,是因为在书序中进行文艺批评是很难把握的;从面对读者的传播效果层面来分析,是因为非文本因素较之文本相关的评论因素可以产生显著的传播效果。于是,非文本因素在文学传播中变成了一位无形的操纵者,虽然它不是长远的传播之道,但却常常起着奇妙的传播作用,从而给书序这一文体增加活力。     

《汉语新词新语年编2003—2005》词目年代研究——兼论《编年本〈汉语新词语〉系列词典部分词目的著录年代》

《汉语新词新语年编2003-2005》一书面世后,陶炼先生发表了《编年本〈汉语新词语〉系列词典部分词目的著录年代》,全文使用《人民日报》报刊检索作为研究新词词目年代的唯一方法。此种方法作为词目搜索范围过于狭窄。为了比较准确查找新词出现的相关年代,应当扩大搜索范围：除使用《人民日报》外．智能查找新词出现年代的方法还可使用人民网等在线报刊网站．利用谷歌、百度等搜索引擎进行网页查找也是可行的方法。新词词目的年代断定在实践中是非常复杂且易出纰满的。新词词典词目年代的断定不能保证完全准确。     

湿蒸汽两相流流量及干度的双参数测量研究

本文采用孔板及均速管组合形式,对汽-水两相流的流量及干度的双参数测量进行了实验研究。实验结果表明,这种测量方法可以满足高干度湿蒸汽测量的要求,具有很好的工业适用性。