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Algorithm 742: L2CXFT: a Fortran subroutine for least-squares data fitting with nonnegative second divided differences
Demetriou I. ACM Transactions on Mathematical Software21 (1):98-110,1995.Type:Article
Date Reviewed: May 1 1996

Demetriou describes an implementation in Fortran 77 of Demetriou and Powell’s algorithm to fit data contaminated with random errors to a convex function. The technique first approximates a solution, then uses quadratic programming with iterative refinement and automatic knot placement on B-splines to find the solution. The technique is useful for large data sets where convexity is assured, and the author cites economic models as a suitable application area. The paper is best seen as an addendum to the original paper [1], describing the practical implementation of the method.

Reviewer:  Tim Thornton Review #: CR119244 (9605-0370)
1) Demetriou, I. C. and Powell, M. J. D. The minimum sum of squares change to univariate data that gives convexity. IMA J. Numer. Anal. 11, 3 (1991), 433–448.
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Least Squares Approximation (G.1.2 ... )
 
 
Optimization (G.1.6 )
 
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