摘要
提出了扩散极大似然估计方法 ,利用实际观测值的概率密度函数的信息扩散估计 ,代替了对观测值分布的主观假设 ,从而具有很强的自适应性。最后设计了两个算例 ,说明了扩散极大似然估计的过程 。
This paper introduces the principle of information diffusion and information diffusion estimation (IDE). And with IDE, the observation distribution can be estimated easily. Once the observation distribution is determined, the parameters can be estimated with the maximum likelihood. With IDE as the basis, the diffusion maximum likelihood (DML) estimation is presented. DML is supposed to enjoy priority because of its being free from any supposition of observation distribution. With two simulative persuasive examples, the high self-adapting and robustness of DML are discussed.
出处
《武汉大学学报(信息科学版)》
EI
CSCD
北大核心
2003年第5期562-565,共4页
Geomatics and Information Science of Wuhan University
基金
国家自然科学基金资助项目 (4 98740 0 2 )
国家测绘局测绘科技发展基金资助项目 (990 10)
关键词
信息扩散
极大似然估计
参数估计
窗宽
测量平差
information diffusion
maximum likelihood estimation
parameter estimation
window-width