Mathematical Sciences: RUI: Partition Study for Successive Difference Analysis

数学科学：RUI：连续差分分析的划分研究

• 批准号: 8706072
• 负责人: Neil Schwertman
• 金额: --
• 依托单位: California State University-Chico
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1987
• 资助国家: 美国
• 起止时间: 1987-06-15 至 1989-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=8706072&HistoricalAwards=false
• 关键词: Mathematical; Sciences; RUI; Partition; Study

This research is to attack the thorny problem of analyzing data that comes from measurements made, or observed, repeatedly but not regularly over time. A novel approach using successive differences is proposed as the basis for analysis assuming piece- wise linearity in the interval of varying lengths. The question to be studied is how to decide where to subdivide the time interval. The traditional methods for analyzing data which is collected repeatedly over time were developed to answer questions posed by the financial community. Financial data is not missing and can be collected at regular fixed time intervals. Because of the structure available in the data driving the early developments in this subfield, the assumptions of a fixed and rigid data structure is built into these analytic approaches. In many fields of research, however, data cannot be collected according to a fixed time schedule as can be done when measuring dollars and cents. Radically new methods of analysis are needed to obtain valid tools for such data, in as much as conclusions are being drawn and decisions based on results from very ad hoc analytical procedures. This research aims to work toward a statistical theory that will be valid for this general framework of scientific investigation.

这项研究是为了解决分析数据的棘手问题，这些数据来自重复但不定期进行的测量或观察。提出了一种新的方法，使用连续的差异作为分析的基础，假设在不同长度的区间分段线性。要研究的问题是如何确定在何处细分时间间隔。分析数据的传统方法是随着时间的推移重复收集的，旨在回答金融界提出的问题。财务数据不会丢失，可以定期收集。由于数据中可用的结构推动了这一子领域的早期发展，因此这些分析方法中内置了固定和刚性数据结构的假设。然而，在许多研究领域，数据不能按照固定的时间表收集，而在衡量美元和美分时可以这样做。需要采用全新的分析方法，以便为这些数据获得有效的工具，因为目前正在根据非常特别的分析程序得出的结果作出结论和决定。这项研究的目的是朝着一个统计理论，这将是有效的科学调查的一般框架。