TOTAL LEAST-SQUARES - STATE-OF-THE-ART REGRESSION IN NUMERICAL-ANALYSIS

被引：66
作者：
NIEVERGELT, Y
机构：
[1] Eastern Washington Univ, Cheney, WA
来源：
SIAM REVIEW | 1994年 / 36卷 / 02期
关键词：
REGRESSION; TOTAL LEAST SQUARES; SINGULAR VALUE DECOMPOSITION;
D O I：
10.1137/1036055
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
Total least squares regression (TLS) fits a line to data where errors may occur in both the dependent and independent variables. In higher dimensions, TLS fits a hyperplane to such data. The elementary algorithm presented here fits readily in a first course in numerical linear algebra.
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页码：258 / 264
页数：7
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