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

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页码：619 / 629

页数：11

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