Adaptive nonparametric regression - a nonasymptotic approach

自适应非参数回归 - 一种非渐近方法

• 批准号: 238442-2010
• 负责人: Levit, Boris
• 金额: $ 1.09万
• 依托单位: Queen's University
• 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=524334
• 关键词: Adaptive; nonparametric; regression; nonasymptotic; approach

When observations of an unknown function contain random errors, the problem of recovering the function is known as Regression. If the function cannot be described by a finite number of parameters, it is a Nonparametric Regression. In this proposal, we pursue several goals essential for the future success of this theory.

当未知函数的观测值包含随机误差时，恢复函数的问题称为回归。如果函数不能用有限数量的参数来描述，则它是非参数回归。在这个建议中，我们追求这个理论未来成功所必需的几个目标。