A versatile, systematic, and efficient line-fitting algorithm is presented, accommodating (1) errors in both coordinates ('errors in the variables'), (2) correlation between the noise in the two coordinates (i.e., equal noise density ellipses that are not aligned with the coordinate axes), (3) heter
✦ LIBER ✦
An extended Marquardt-type procedure for fitting error-in-variables models
✍ Scribed by P. Valkó; S. Vajda
- Publisher
- Elsevier Science
- Year
- 1987
- Tongue
- English
- Weight
- 704 KB
- Volume
- 11
- Category
- Article
- ISSN
- 0098-1354
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The Error-in-Variables Model (EVM) provides a means for estimating parameter values in mathematical models where there is error in every measured variable. This is a distinct improvement over the Method of Least Squares in most situations because the latter requires that there be error in measuring