SBIR PHASE II: Statistical Analysis and Software for Long Memory Processes

布鲁斯酒店 这个小企业创新研究第二阶段项目将对长记忆过程的统计方法进行新的创新研究。 这些过程可用于模拟在物理学、海洋学、天文学、经济学、生理学和其他学科中经常遇到的时间序列。 长记忆过程的本质是，随着时间间隔的增加，观察结果之间的相关性会缓慢下降。 使用标准时间序列方法可能导致不正确的统计分析;例如，平均值的置信区间可能小得不切实际。 这个研究项目将为长记忆过程的完整方法学做出重要的进展，这是对科学的基本贡献。 最终的目标是实施的研究和现有的方法到一个面向对象的软件工具包建模长记忆时间序列，供广泛的统计学家，数据分析师和科学家使用。 如果成功的话，这项研究将导致一个软件工具包，提供完整的统计方法来建模长记忆时间序列。 该工具包将作为S-PLUS模块以及MathCAD功能包和电子书销售。 此外，将单独编制和销售一本从业人员案例手册。 ***

*** 9801614 Bruce This Small Business Innovation Research Phase II project will conduct new and innovative research into statistical methodology for long memory processes. These processes can be used to model time series commonly encountered in geophysics, oceanography, astronomy, economics, physiology and other disciplines. The essence of a long memory process is that correlation between observations decreases slowly as separation in time increases. Use of standard time series methodology with these can lead to incorrect statistical analysis; e.g., confidence intervals for the mean can be unrealistically small. This research project will make important advances toward a complete methodology for long memory processes, a fundamental contribution to science. The ultimate objective is to implement the research and existing methodology into an object-oriented software tool kit for modeling long memory time series for use by a broad range of statisticians, data analysts and scientists. If successful, the research will lead to a software tool kit offering complete statistical methodology for modeling long memory time series. The tool kit will be marketed as an S-PLUS module and as a MathCAD function pack and electronic book. In addition, a practitioner's casebook of examples will be developed and marketed separately. ***