Statistical learning for recommending (robust) nonlinear regression methods
We are interested in comparing the performance of various nonlinear estimators of parameters of the standard nonlinear regression model. While the standard nonlinear least squares estimator is vulnerable to the presence of outlying measurements in the data, there exist several robust alternatives. H...
Main Authors: | Kalina J., Tichavský J. |
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Format: | Article |
Language: | English |
Published: |
Sciendo
2019-12-01
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Series: | Journal of Applied Mathematics, Statistics and Informatics |
Subjects: | |
Online Access: | http://www.degruyter.com/view/j/jamsi.2019.15.issue-2/jamsi-2019-0008/jamsi-2019-0008.xml?format=INT |
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