Incomplete orthogonal distance regression

被引：3
|
作者：
Atieg, A [1 ]
Watson, G [1 ]
机构：
[1] Univ Dundee, Dept Math, Dundee DD1 4HN, Scotland
来源：
BIT NUMERICAL MATHEMATICS | 2004年 / 44卷 / 04期
关键词：
least squares; orthogonal distances; Gauss-Newton method;
D O I：
10.1007/s10543-004-6023-9
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
A common method of fitting curves and surfaces to data is to minimize the sum of squares of the orthogonal distances from the data points to the curve or surface, a process known as orthogonal distance regression. Here we consider fitting geometrical objects to data when some orthogonal distances are not available. Methods based on the Gauss-Newton method are developed, analyzed and illustrated by examples.
引用
收藏
页码：619 / 629
页数：11
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