Comparison of computer programs for simple linear L 1 regression

A number of efficient computer codes are available for the simple linear L ₁ regression problem. However, a number of these codes can be made more efficient by utilizing the least squares solution. In fact, a couple of available computer programs already do so.

We report the results of a computational study comparing several openly available computer programs for solving the simple linear L ₁ regression problem with and without computing and utilizing a least squares solution.     

Bayesian adaptive dose‐escalation designs for simultaneously estimating the optimal and maximum safe dose based on safety and efficacy

The main purpose of dose‐escalation trials is to identify the dose(s) that is/are safe and efficacious for further investigations in later studies. In this paper, we introduce dose‐escalation designs that incorporate both the dose‐limiting events and dose‐limiting toxicities (DLTs) and indicative responses of efficacy into the procedure. A flexible nonparametric model is used for modelling the continuous efficacy responses while a logistic model is used for the binary DLTs. Escalation decisions are based on the combination of the probabilities of DLTs and expected efficacy through a gain function. On the basis of this setup, we then introduce 2 types of Bayesian adaptive dose‐escalation strategies. The first type of procedures, called “single objective,” aims to identify and recommend a single dose, either the maximum tolerated dose, the highest dose that is considered as safe, or the optimal dose, a safe dose that gives optimum benefit risk. The second type, called “dual objective,” aims to jointly estimate both the maximum tolerated dose and the optimal dose accurately. The recommended doses obtained under these dose‐escalation procedures provide information about the safety and efficacy profile of the novel drug to facilitate later studies. We evaluate different strategies via simulations based on an example constructed from a real trial on patients with type 2 diabetes, and the use of stopping rules is assessed. We find that the nonparametric model estimates the efficacy responses well for different underlying true shapes. The dual‐objective designs give better results in terms of identifying the 2 real target doses compared to the single‐objective designs.     

Estimation of the parameter of a dynamically selected population for two subclasses of the exponential family

We introduce the problem of estimation of the parameters of a dynamically selected population in an infinite sequence of random variables and provide its application in the statistical inference based on record values from a non stationary scheme. We develop unbiased estimation of the parameters of the dynamically selected population and evaluate the risk of the estimators. We provide comparisons with natural estimators and obtain asymptotic results. Finally, we illustrate the applicability of the results using real data.     

社会化网络3维用户界面设计分析与研究

为了寻找三维用户界面设计策略，在归纳2维（2D）与2．5维（2．5D）用户界面包含的内容与设计策略的基础上，从3维（3D）用户界面的交互任务、信息呈现和用户搜索行为三方面进行了分析，整合了用户需求、空间行为、空间任务，创新性地构建了面向真3D空间的“需求-任务-层次模型”，为3D用户界面的构建提供了新的思路。此外，从细节层面对3D用户界面具体设计原则进行分析，提出了“信息呈现设计矩阵”，对3D用户界面设计具有一定的指导意义。     

An economic model for the quality selection problem

The object of an economic model for the quality selection problem is to select the best parameter value for an input quality characteristic (X) so that the quality loss incurred on an output quality characteristic (Y) is minimized. The relation function between Y and X is assumed to be known throughout the article. In the work of Taguchi's experimentations, the selection of best parameter values is solved by two-step optimization when Y is adjustable. In the article, it is further extended to the case where Y is non-adjustable. An economic quality selection model with a general relation function is proposed based on a Taylor-series method for both adjustable and non-adjustable cases. A special case of a quality selection model with a quadratic relation function is also studied. A circuit example provided by Taguchi is presented to illustrate the use of this model.     

A monte carlo evaluation of response surface analysis based on paired-comparison data

The use of the logit transformation on paired-comparison data in the weighted least squares analysis of response surfaces for aesthetic qualities of products is discussed. Monte Carlo simulations are employed to investigate the small sample properties of the estimators and test statistics. A secondary objective of the Monte Carlo simulations is the comparison of two transformation procedures. The simulations are of standard-item paired-compar-ison experiments in which ties are not allowed.     

居民发展能力评估与差异比较——以甘肃省张掖市、甘南自治州为例

阿玛帝业森的能力理论是有关人类文化发展、福利经济学、社会政策研究的哲学论述,是有关个体福利和生活质量评估、社会整顿、政策制定和社会改革等的标准分析框架。本文在简要介绍阿玛帝亚森能力分析的概念和评估方法之后,采用社会学研究方法,通过问卷调查,以黑河流域张掖市与甘南自治州城市居民的能力分析测定为例,尝试在国内开展能力分析的定量研究,并比较影响两地区居民能力的主要因素,分析了提升个体能力,开展能力分析研究的重要意义。     

成人高等教育教学管理模式改革的思考

目前成人高等教育在教学管理中仍然存在许多不足，结合我院成人学生教学管理所取得的成绩和经验，针对当前所面临的现状和问题，指出应进一步深化成人学生教学管理模式改革，并提出了相应的对策措施。     

On the α-risks for shewhart control charts

The performance of the usual Shewhart control charts for monitoring process means and variation can be greatly affected by nonnormal data or subgroups that are correlated. Define the α_k-risk for a Shewhart chart to be the probability that at least one “out-of-control” subgroup occurs in k subgroups when the control limits are calculated from the k subgroups. Simulation results show that the α_k-risks can be quite large even for a process with normally distributed, independent subgroups. When the data are nonnormal, it is shown that the α_k-risk increases dramatically. A method is also developed for simulating an “in-control” process with correlated subgroups from an autoregressive model. Simulations with this model indicate marked changes in the α_k-risks for the Shewhart charts utilizing this type of correlated process data. Therefore, in practice a process should be investigated thoroughly regarding whether or not it is generating normal, independent data before out-of-control points on the control charts are interpreted to be due to some real assignable cause.     

Collapsibility of Conditional Graphical Models

Abstract. In this paper, we consider two kinds of collapsibility, that is, the model‐collapsibility and the estimate‐collapsibility, of conditional graphical models for multidimensional contingency tables. We show that these two definitions are equivalent, and propose a sufficient and necessary condition for them in terms of the interaction graph, which allows the collapsibility to be characterized and judged intuitively and conveniently.