On the accuracy of total least squares and least squares techniques in the presence of errors on all data
β Scribed by Sabine Van Huffel; Joos Vandewalle
- Publisher
- Elsevier Science
- Year
- 1989
- Tongue
- English
- Weight
- 388 KB
- Volume
- 25
- Category
- Article
- ISSN
- 0005-1098
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β¦ Synopsis
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 (TLS), is devised. This paper investigates, via simulations how perturbations on both A and B affect the accuracy of the TLS and LS solution. Several important factors are discussed, as well as the consistency properties of the TLS solution in the presence of uncorrelated and equally sized errors. *
π SIMILAR VOLUMES
One of the methods in common use for analyzing large data sets is a two-step procedure, in which subsets of the full data are first least-squares fitted to a preliminary set of parameters, and the latter are subsequently merged to yield the final parameters. The second step of this procedure is prop
## Abstract Arrhenius parameters are frequently evaluated incorrectly by applying the least squares method to the logarithmic form of the Arrhenius equation without simultaneously transforming the statistical weights as required for the change of variable from __k__ to ln __k__. This has been menti