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基于选择准则的参数模型评价方法
引用本文:段晓君,王正明. 基于选择准则的参数模型评价方法[J]. 国防科技大学学报, 2003, 25(3): 62-65
作者姓名:段晓君  王正明
作者单位:国防科技大学人文与管理学院,湖南,长沙,410073
基金项目:全国优秀博士论文作者专项基金(200140),国防科技大学基础研究项目(JC01-02-001)
摘    要:为评价参数模型的优劣,分析了模型信息量与数据被模型拟合后的残差信息量之间的关系,提出了综合考虑模型拟合残差大小、残差信息量与参数数目的一种模型选择的新方法RIA。结合RIA方法,定义了时序模型评价的一种准则,并以航天测量数据处理为例,说明了不同模型在工程实际中的不同表现和本质区别的意义所在。

关 键 词:残差  信息量  模型选择  模型评价
文章编号:1001-2486(2003)03-0062-04
收稿时间:2002-11-24
修稿时间:2002-11-24

Parametric Model Evaluation Based on the Selection Criterion
DUAN Xiaojun and WANG Zhengming. Parametric Model Evaluation Based on the Selection Criterion[J]. Journal of National University of Defense Technology, 2003, 25(3): 62-65
Authors:DUAN Xiaojun and WANG Zhengming
Affiliation:College of Humanities and Management, National Univ. of Defense Technology, Changsha 410073,China;College of Humanities and Management, National Univ. of Defense Technology, Changsha 410073,China
Abstract:There is no uniform frame for evaluating a parametric model. A new criterion named by RIA for the model selection is presented which synthetically considers the approximation precision, sparsity of parameters and the residual information. Here the residual information with Gauss distribution is measured by relativity of the residual. According to a simple thought that the whole system is comprised of model information and residual information after modeling the data. This new criterion is transformed into a measurement form for model information. And its reasonability is demonstrated here by theoretic analysis with the application in space data processing.
Keywords:residual  information  model selection  model evaluation
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