Summary
We treat the problem of approximating data that are sampled with error from a function known to be convex and increasing. The approximating function is a polynomial spline with knots at the data points. This paper presents results (analogous to those in [7] and [9]) that describe some approximation properties of polynomial splines and algorithms for determining the existence of a “shape-preserving” approximant for given data.
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Formerly of the Graduate Program in Operations Research, NC State University. Author now
Research supported in part by NASA Grant NAG1-103
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Dodd, S.L., McAllister, D.F. Algorithms for computing shape preserving spline approximations to data. Numer. Math. 46, 159–174 (1985). https://doi.org/10.1007/BF01390417
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DOI: https://doi.org/10.1007/BF01390417