Unbiased estimation of a nonlinear function a normal mean with application to measurement err oorf models

Let W be a normal random variable with mean μand known variance σ². Conditions on the function f(·) are given under which there exists an unbiased estimator, f(W), of f(μ) for all real μ. In particular it is shown that f(·) must be an entire function over the complex plane. Infinite series solutions for F(·) are obtained which are shown to be valid under growth conditions of the derivatives, f^k( ·), of f(·). Approximate solutions are given for the cases in which no exact solution exists. The theory is applied to nonlinear measurement-error models as a means of finding unbiased score functions when measurement error is normally distributed. Relative efficiencies comparing the proposed method to the use of conditional scores (Stefanski and Carroll, 1987) are given for the Poisson regression model with canonical link.     

Estimation of a process capability index for inverse gaussian distribution

In this article, interval estimates of Clements' process capability index are studied through bootstrapping when the underlying distribution is Inverse Gaussian. The standard bootstrap, the percentile bootstrap, and the bias-corrected percentile bootstrap confidence intervals are compared.     

On the Choice of Functional Forms: Summary of a Monte Carlo Experiment

The use of flexible functional forms is a standard practice in applied econometrics. Many flexible forms have been proposed. In this study, we investigate the behavior of three of them—the translog, the symmetric McFadden, and the symmetric generalized Barnett. Based on Monte Carlo experiments, we assess the ability of these forms to test theoretical properties and to measure technological characteristics.     

SOJOURN TIMES IN NON-HOMOGENEOUS QBD PROCESSES WITH PROCESSOR SHARING

We study sojourn times of customers in a processor sharing queue with a service rate that varies over time, depending on the number of customers and on the state of a random environment. An explicit expression is derived for the Laplace–Stieltjes transform of the sojourn time conditional on the state upon arrival and the amount of work brought into the system. Particular attention is paid to the conditional mean sojourn time of a customer as a function of his required amount of work, and we establish the existence of an asymptote as the amount of work tends to infinity. The method of random time change is then extended to include the possibility of a varying service rate. By means of this method, we explain the well-established proportionality between the conditional mean sojourn time and required amount of work in processor sharing queues without random environment. Based on numerical experiments, we propose an approximation for the conditional mean sojourn time. Although first presented for exponentially distributed service requirements, the analysis is shown to extend to phase-type services. The service discipline of discriminatory processor sharing is also shown to fall within the framework.     

Multistage sampling for latent variable models

I consider the design of multistage sampling schemes for epidemiologic studies involving latent variable models, with surrogate measurements of the latent variables on a subset of subjects. Such models arise in various situations: when detailed exposure measurements are combined with variables that can be used to assign exposures to unmeasured subjects; when biomarkers are obtained to assess an unobserved pathophysiologic process; or when additional information is to be obtained on confounding or modifying variables. In such situations, it may be possible to stratify the subsample on data available for all subjects in the main study, such as outcomes, exposure predictors, or geographic locations. Three circumstances where analytic calculations of the optimal design are possible are considered: (i) when all variables are binary; (ii) when all are normally distributed; and (iii) when the latent variable and its measurement are normally distributed, but the outcome is binary. In each of these cases, it is often possible to considerably improve the cost efficiency of the design by appropriate selection of the sampling fractions. More complex situations arise when the data are spatially distributed: the spatial correlation can be exploited to improve exposure assignment for unmeasured locations using available measurements on neighboring locations; some approaches for informative selection of the measurement sample using location and/or exposure predictor data are considered.     

腐败的主观测评方法——以腐败感知指数为例

腐败测评是反腐败研究的重要组成部分,中国的腐败测评体系亟待发展。腐败测评有主观测评法和客观测评法两种研究思路。从统计机理和统计应用情况看,腐败的主观测评方法处于腐败测评研究的主流地位。本文介绍了腐败主观测评方法的基本思路、研究进展,并以腐败感知指数为例对其理论与应用情况进行了说明。     

一种适用于NGSO MSS网络的混合信道分配方案

针对ＮＧＳＯＭＳＳ网络的动态特性,提出了一种适用于该网络的混合信道分配方案。在该方案中,固定信道采用非均匀压缩图案分配算法分配给各小区作为标称信道专用,并定期根据变化了的业务条件进行重新分配,动态信道的指派采用最先可行ＦＡ（ＦｉｒｓｔＡｖａｉｌａｂｌｅ）算法。仿真结果表明,在较宽的负载范围内,运用该方案比固定信道分配方案均有更好的性能,并能有效地降低切换呼叫和信道更新期间的呼损率,从而显著提高网络的业务承载量。     

论充分发挥教学秘书的服务与管理职能

积极努力、主动热情、严谨求实、理解与宽容、牺牲与奉献,是高校教学秘书的基本素质与要求;变被动服务为主动服务,是提高服务质量的重要标志;实施科学管理,是教学秘书的历史使命;学习教育管理理论,是教学秘书提高服务质量的重要保证。     

网络视频实时在线评论用户认可度的影响因素

目前,网络视频实时在线评论激增带来的信息爆炸,使实时在线评论信息管理成为重要议题。以往对实时在线评论的研究多集中于个人行为结果方面,而缺乏对实时在线评论信息管理问题的关注;同时,现有视频网站对实时在线评论信息的管理也存在诸多局限。以爱奇艺视频网站热度榜中的电影为样本,基于信息质量维度框架并采用Tobit模型对实时在线评论用户认可度的影响因素进行研究,结果发现：实时在线评论的新颖性、相似性、情感倾向性和信息丰富性,均对实时在线评论的用户认可度存在显著影响,其中新颖性和相似性影响作用最大。视频网站可以据此进一步强化实时在线评论管理,改善用户的体验,保持用户的粘性。