Tree-Structured Statistical Methods

树形结构统计方法

• 批准号: 9101548
• 负责人: Richard Olshen
• 金额: $ 7.44万
• 依托单位: Stanford University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1991
• 资助国家: 美国
• 起止时间: 1991-08-01 至 1995-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9101548&HistoricalAwards=false
• 关键词: Tree; Structured; Statistical; Methods

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.

主要研究者将研究统计方法。 这些 涉及二元问题序列的最佳选择， 分类问题，概率类估计， 回归和生存分析。 大部分电脑- 计划中的密集研究涉及新的能力， 给出的算法和技术的显著改进 作者：Breiman，Friedman，Olshen，and Stone in Classification and 回归树及其相关的CART软件。 一些 计算将以创新的分布式模式在一个 工作站系统。 调查人员计划申请， 测试数据集，特别是关于 快速诊断心脏病 详细介绍了一个 应用于增强某些磁共振 对患者进行诊断很重要的图像 淋巴瘤 （不要求支持开展临床研究） 试验;事实上，这些数据不是来自传统的临床试验， 审判。） 所涉及的统计研究对一个 广泛的应用，其中一些是医疗。