Reliability, Statistical Applications of Order Restricted Methods

布洛克、桑普森和萨维茨9704400这项研究的重点是为统计和可靠性领域面临的一些主要问题发展方法论和理论。一个主要的重点是关于老化的话题。正在进行的研究包括确定分布类别和成本结构族的最优老化。特别令人感兴趣的是具有浴缸形状风险函数的分布族。这项研究的第二个主要重点是发展方法，以支持在涉及多变量观测的数据分析中使用现代顺序限制推理的非参数思想。对于顺序限制推理，已经发展了大量的理论；然而，这里的研究重点是将其中一些结果用于重要的估计和测试问题，部分地由研究人员获得的一些计算结果的应用来支持。这项研究在现代数据分析中有效地利用了这类优雅的非参数程序。另外两个研究领域是进一步发展加速退化实验产生的数据的模型和方法，以及继续发展随机长度多变量数据的建模。这四个研究领域在处理不同问题的同时，运用了可靠性、顺序限制推理和多元分析等相关领域的理论和方法。老化是一种广泛使用的工程实践，通过在发布销售或使用之前消除薄弱的工业产品来提高可靠性。这是许多现代美国工业过程中的一个重要话题。正在开发统计工具，以执行新的生产战略，这些战略有助于确定如何处理可能在关键用途早期失效的物品。成本效益高的新生物工程药物的临床开发通常需要确定哪些患者更适合使用新生物药物，而不是使用标准的现有治疗方法。其中一些研究的重点是开发改进的统计技术，以更好地识别那些将从新的生物技术中显著受益的患者。这项研究的其他方面包括获得更有效的统计方法，使临床医生能够预测特定患者对新疗法成功反应的可能性。

Block, Sampson and Savits 9704400 This research focuses on the development of methodology and theory for some major problems facing the statistics and reliability communities. One major emphasis is on the topic of burn-in. On-going research involves determining optimal burn-in for classes of distributions and families of cost structures. Of particular interest is the family of distributions with bathtub shaped hazard functions. A second major emphasis of this research is in the development of methods to support the use of the modern nonparametric ideas of order restricted inference in data analysis involving multivariate observations. A great deal of theory has been developed for order restricted inference; however, the research focus here is to utilize some of these results in important estimation and testing problems, in part, supported by the application of some of the computational results obtained by the investigators. This research makes effective use of this elegant class of nonparametric procedures in modern data analysis. Two other areas of research are the further development of models and methodologies for data arising from accelerated degradation experiments, and the continued development of the modeling of random length multivariate data. These four research areas, while dealing with varied problems, utilize theory and methods from the allied areas of reliability, order restricted inference and multivariate analysis. Burn-in is a widely used engineering practice for increasing reliability by eliminating weak industrial products before they are released for sale or use. This is an important topic in many modern American industrial processes. Statistical tools are being developed to implement new production strategies which are useful in determining how to deal with items which might fail early in critical uses. The clinical development of cost-effective new bioengineered pharmaceuticals often requires identification of those patients who would b enefit substantially more from new biopharmaceuticals than from standard available treatments. Some of this research focuses on developing improved statistical techniques to better identify those patients who would significantly benefit from the new biotechnology. Other aspects of the research involve obtaining more effective statistical approaches to allow clinicians to predict the likelihood of specific patients having a successsful response to a new treatment.