Accession Number:

ADP011967

Title:

Extending Lawson's Algorithm to Include the Huber M-Estimator

Descriptive Note:

Conference paper

Corporate Author:

HUDDERSFIELD UNIV (UNITED KINGDOM) SCHOOL OF COMPUTING AND MATHEMATICS

Personal Author(s):

• Anderson, Iain J.
• Mason, John C.
• Ross, Colin

Report Date:

2000-01-01

Pagination or Media Count:

8.0

Abstract:

When fitting a curve to experimental data, there is no guarantee that the data obtained are as accurate as might be expected. The effect of outside influences may cause the data set to contain outliers. These outliers can have a significant effect on any curve which is fitted to such data. The l infinity-norm, which is particularly appropriate for fitting data with uniformly distributed errors, is extremely sensitive to such outliers, since it minimises the maximum error from the data to the curve. Therefore, a technique which approximates a data set using the l infinity-norm, without being adversely affected by outliers, would be a useful addition to the array of tools available. We present numerical examples to illustrate the use of such a technique and also some practical applications to justify its use.

Descriptors:

• *CURVE FITTING
• ALGORITHMS
• APPROXIMATION(MATHEMATICS)
• UNITED KINGDOM

Subject Categories:

• Numerical Mathematics
• Theoretical Mathematics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE