Inference in the presence of constraints

存在约束条件下的推理

• 批准号: 138127-2009
• 负责人: Braun, Willard
• 金额: $ 1.38万
• 依托单位: University of Western Ontario
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2013
• 资助国家: 加拿大
• 起止时间: 2013-01-01 至 2014-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=522358
• 关键词: Inference; presence; constraints

One of the main goals of this project is to improve curve and surface estimation when data are limited but when input from scientific experts is available. A number of smoothing techniques exist for flexibly modeling data, and these techniques have good properties. It is possible to apply these techniques to forms of data which have been adjusted according to previously available science. Depending on the accuracy of the science, the resulting estimates should be better than those obtained from the unadjusted data. The technique of modifying the data, taking into account qualitative information, is called data sharpening. By employing data sharpening, scientists should be able to obtain improved estimates of quantities they are interested in (usually in the form of curves and surfaces), and they should also be able to obtain better predictions as a result. Software for data sharpening will be developed in order to handle a wide variety of modeling problems.

该项目的主要目标之一是在数据有限但可获得科学专家输入的情况下改进曲线和曲面估计。存在许多用于灵活建模数据的平滑技术，并且这些技术具有良好的特性。可以将这些技术应用于已根据先前可用的科学进行调整的数据形式。根据科学的精确度，由此得出的估计应该比从未经调整的数据获得的估计更好。考虑到定性信息来修改数据的技术称为数据锐化。通过使用数据锐化，科学家应该能够改进对他们感兴趣的量的估计(通常是以曲线和曲面的形式)，因此他们也应该能够获得更好的预测。将开发数据锐化软件，以处理各种建模问题。