Tree-Structured Statistical Methods

首席调查员将研究统计方法。这些问题涉及分类、概率类估计、回归和生存分析问题的二元问题序列的最佳选择。计划中的许多计算机密集型研究涉及Breiman、Friedman、Olshen和Stone在分类和回归树及其相关CART软件中提供的算法和技术的新功能和重大改进。一些计算将在工作站系统上以创新的分布式模式进行。研究人员计划应用程序来测试数据集，特别是关于心脏病发作快速诊断的大型数据集。给出了增强某些磁共振图像的应用的细节，这些图像对于淋巴瘤患者的预后很重要。(不需要为临床试验的进行提供支持；事实上，这些数据不是来自传统的临床试验。)所涉及的统计研究对广泛的应用具有重要意义，其中一些应用是医学应用。

The Principal Investigator will study statistical methods. These involve the optimal choices of sequences of binary questions for problems of classification, probability class estimation, regression, and survival analysis. Much of the computer- intensive research that is planned involves new capabilities and significant improvements of the algorithms and techniques given by Breiman, Friedman, Olshen, and Stone in Classification and Regression Trees and its associated CART software. Some computations will be done in an innovative distributed mode on a system of workstations. The investigators plan applications to test data sets, particularly a large data set concerning the quick diagnosis of heart attack. Details are given for an application to the enhancement of certain magnetic resonance images that are important to making prognoses for patients with lymphoma. (Support is not requested for the conduct of clinical trials; indeed, the data do not arise from conventional clinical trials.) The statistics research involved is of importance to a wide variety of applications, some of them medical.