Robust regression and outlier detection for non-linear models using genetic algorithms

Chemometrics and Intelligent Laboratory Systems

Volumn 28, Issue 1, 1995, Pages 73-87

  Vankeerberghen, P ^a   Smeyers Verbeke, J ^a   Leardi, R ^b   Karr, C L ^c   Massart, D L ^a  

^a PHARMACEUTICAL INSTITUTE   (Belgium)

^b UNIVERSITY OF GENOA   (Italy)

^c US Bureau of Mines   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; CALIBRATION; CHEMOMETRICS; CONFERENCE PAPER; PHARMACOKINETICS; PRIORITY JOURNAL;

EID: 0028915326     PISSN: 01697439     EISSN: None     Source Type: Journal    
DOI: 10.1016/0169-7439(95)80041-7     Document Type: Article

References (23)

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2. A rank-invariant method of linear and polynomial regression analysis (Parts 1–3), Nederlandse Akademie voor Wetenschappen
3. A rank-invariant method of linear and polynomial regression analysis (Parts 1–3), Nederlandse Akademie voor Wetenschappen
4. A rank-invariant method of linear and polynomial regression analysis (Parts 1–3), Nederlandse Akademie voor Wetenschappen
5. Robust regression using repeated medians
6. Least median of squares regression
7. A general qualitative definition of robustness
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9. Genetic algorithms
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11. An overview of genetic algorithms: Part 1
12. A note on the generation of random normal deviates
13. A hybrid genetic algorithm for the estimation of kinetic parameters
14. Modelling chromatographic behaviour as a function of pH and solvent composition in RPLC
15. Curve fitting using natural computation
16. Distributing a computationally intensive estimator: the case of the exact LMS regression