Optimality Conditions for Best Ll Data Fitting subject to Nonnegative Second Differences

If plotted values of measurements of function values show some gross errors and away from them the function seems to be convex, then it is suitable to make the least sum of absolute change to the data subject to the condition that the second divided differences of the smoothed data are non-negative....

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Bibliographic Details
Published inIAENG international journal of applied mathematics Vol. 38; no. 1; pp. 30 - 33
Main Authors Papakonstantinou, S S, Demetriou, I C
Format Journal Article
LanguageEnglish
Published 01.03.2008
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ISSN1992-9978
1992-9986

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Summary:If plotted values of measurements of function values show some gross errors and away from them the function seems to be convex, then it is suitable to make the least sum of absolute change to the data subject to the condition that the second divided differences of the smoothed data are non-negative. The constraints enter by the assumption of non-decreasing returns of the underlying function, which implies convexity. It is a highly structured constrained Ll approximation problem, which can be expressed as a linear programming calculation. Necessary and sufficient conditions for a solution to this Ll problem are presented.
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ISSN:1992-9978
1992-9986