This paper describes a procedure for optimal rounding of parameters determined from a linear or nonlinear least-squres fit in order to minimize the number of digits which must be quoted while ensuring that the resulting rounded constants can predict the input data with no significant loss of precisi
Rounding errors in the reporting of least-squares parameters
β Scribed by James K.G. Watson
- Publisher
- Elsevier Science
- Year
- 1977
- Tongue
- English
- Weight
- 193 KB
- Volume
- 66
- Category
- Article
- ISSN
- 0022-2852
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π SIMILAR VOLUMES
The numerical robustness of four generallyapplicable, recursive, least-squares estimation schemes is analysed by means of a theoretical round-off propagation study. This study highlights a number of practical, interesting ins;.ghts into the widely-used recursive least-squares schemes. These insights
Abstroct~Every linear parameter estimation problem gives rise to an overdetermined set of linear equations AX ~ B which is usually solved with the ordinary least squares (LS) method. Often, both A and B are inaccurate. For these cases, a more general fitting technique, called total least squares (TL