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Least-squares Polynomial Estimation from

✍ Scribed by R. Caballero-Águila; A. Hermoso-Carazo; J. Linares-Pérez


Publisher
Springer US
Year
2009
Tongue
English
Weight
416 KB
Volume
12
Category
Article
ISSN
1387-5841

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## Abstract Maximum likelihood fit of nonlinear, implicit, multiple‐response models to data containing normally distributed random errors can be carried out by a combination of the Gauss‐Newton generalized nonlinear least‐square algorithm first described by Britt and Luecke in 1973, with a Fletcher