On the risk performance of extended sequence compound rules for classification between N(–1, 1) and N(1, 1) †

Since Robbins (1951) first introduced the compound decision problem, there has evolved a large literature on the subject for the most part dealing with the construction of compound rules whose excess risk over the simple envelope is no greater than zero in the limit as the number N of component problems goes to infinity. Such rules have compound risk which is asymptotically subminimax. Johns (1967) has introduced more stringent (extended) envelopes and has proposed extended compound rules whose risks achieve these envelopes in the limit. This paper reports some Monte Carlo results on the compound risk behavior of selected unextended and extended rules for moderate N values and certain parameter sequences for Robbins original example. The results show that the extended rules compare favorably with the minimax rule and the unextended rules for moderate N and parameter sequences exhibiting higher order empirical dependencies, for example, those generated by a Markov process.     

Study design of single‐arm phase II immunotherapy trials with long‐term survivors and random delayed treatment effect

In the traditional study design of a single‐arm phase II cancer clinical trial, the one‐sample log‐rank test has been frequently used. A common practice in sample size calculation is to assume that the event time in the new treatment follows exponential distribution. Such a study design may not be suitable for immunotherapy cancer trials, when both long‐term survivors (or even cured patients from the disease) and delayed treatment effect are present, because exponential distribution is not appropriate to describe such data and consequently could lead to severely underpowered trial. In this research, we proposed a piecewise proportional hazards cure rate model with random delayed treatment effect to design single‐arm phase II immunotherapy cancer trials. To improve test power, we proposed a new weighted one‐sample log‐rank test and provided a sample size calculation formula for designing trials. Our simulation study showed that the proposed log‐rank test performs well and is robust of misspecified weight and the sample size calculation formula also performs well.     

A Non-Typical Least-Squares Solution to an Engineering Problem

In preposterior analysis, Bayesians use an Expected-Net-Gain chart to identify the optimal sample size. This kind of chart, it turns out, is also an excellent educational vehicle for illustrating many of the reasons given for preferring sampling from a population over taking a census, preferring one type of sampling over another (e.g., stratified sampling rather than simple random sampling), or allocating part of a fixed budget to reduce systematic error rather than using it all to reduce sampling errors. The use of such a chart in a basic statistics course is described.     

Monitoring long-term clinical trials for beneeficial and adverse treatment effects

When the data from a long-term clinical trial are reviewed continually over time for evidence of adverse or beneficial treatment effects, the classical significance tests are not appropriate. A simulation procedure is described which provides the correct critical regions corresponding to specified frequencies of data reviews over the course of the trial. Several different types of critical boundaries (e.g., horizontal, sloping,stepped, and asymmetric) are compared with respect to statistical power and closeness to the classical critical values at the final data review.     

联系度在决策中的应用

介绍了集对分析的一个重要概念——联系度，讨论了用联系度进行单个方案决策及多个方案评优决策的方法。     

建立法官、民意与判文解释三位一体的刑事司法适用机制——化解司法和民意冲突的第三条道路

在我国,司法解释权是一种相对独立的权力,判文解释不属于司法解释,因而不具有司法解释的效力。在现实生活中,法官的能动性常常受到抑制,多数法官只是机械地适用法律,这就远远不能适应千变万化的社会现实的司法需求。这样一来,严格依法办事的结果与＂民意＂相背的情形难以避免。在现代社会中,如何吸纳民意已成为民众参与社会管理、参与司法和对司法实施监督的重要问题。鉴于此,正确认识司法实践中运用判文解释的必然性,探讨其与吸纳民意的内在关系,并通过法官建构判文解释以有效吸纳民意,是化解社会矛盾和司法现代化的重要课题。     

数据挖掘在高校成绩分类管理中的应用研究

学生的信息是大量的和复杂的，学校越来越感到管理的复杂性，对于学生的状态和发展越来越难以预测，因此学校希望对学生海量数据的处理不只是简单的备份和查询，而更迫切地需要管理信息系统能够具备辅助决策的能力。应用数据挖掘技术对学生成绩分类管理进行探索，获得有益的隐含知识，支持学生工作和教学管理工作的开展，这对于素质教育的实施，更好地为学生服务提供了很好的尝试。     

公路项目投资决策指标体系与评价方法

为从理论上研究多种因素影响下的公路项目投资决策问题,从技术、经济、环境三个方面为公路项目建立了一套适用性较强的评价指标体系,运用方差最大化法确定指标体系中定量指标的权重,对社会效益这一定性指标选用层次分析法和模糊综合评判法相结合的方法进行分析,最后将各个指标进行综合评价。实例分析结果表明：该指标体系和评价方法具有很强的实用性和可操作性。     

模式识别课程中的统计学方法概述

模式识别是近年来迅速发展的一门学科,在工业、信息处理等领域有广泛应用。本文对模式识别、模式识别与统计学的关系进行了简单介绍,同时介绍了模式识别课程中两种基本的统计学方法：贝叶斯统计决策理论及概率密度估计理论。