摘要
本文给出多元线性模型协差阵基于LSE无偏估计的影响函数,得出其对数据点异常值不具有稳健性的结论,为对其进行数据点影响分析奠定了理论基础;提出一种影响度量,对于正态模型,优于已有的似然距离.计算了一个实例.
The necessity to make case - influence analysis is proved for the LSE-based unbiased estimate of covariance matrix in multivari-ate linear model following the derivation of its influence function, -which is never seen elsewhere. A statistic, not only intuitive but also easy to calculate , is suggested to measure the influence exerted by a certain data set-Far a normally distributed model , the new criterion with its distributionknown, is more accurate in discerning powerful influential sets than themeasure likelihood distance, for whose distribution no succinct form isavailable- An illustrative example is given.
出处
《苏州大学学报(自然科学版)》
CAS
1996年第2期45-50,共6页
Journal of Soochow University(Natural Science Edition)
关键词
最小二乘估计
多元线性模型
无偏估计
影响函数
LSE (Least Squares Estimate),Statistical Functional, Influence Function, Likelihood Distance,Wilks's ∧