Journal of Global Optimization

, Volume 66, Issue 1, pp 111–126 | Cite as

Maximum consistency method for data fitting under interval uncertainty

  • Sergey P. Shary


The work is devoted to application of global optimization in data fitting problem under interval uncertainty. Parameters of the linear function that best fits intervally defined data are taken as the maximum point for a special (“recognizing”) functional which is shown to characterize consistency between the data and parameters. The new data fitting technique is therefore called “maximum consistency method”. We investigate properties of the recognizing functional and present interpretation of the parameter estimates produced by the maximum consistency method.


Data fitting Interval uncertainty Recognizing functional Maximum consistency Nonconvex optimization 

Mathematics Subject Classification

62H99 93B30 90C26 


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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.Institute of Computational TechnologiesNovosibirskRussia

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