Note—A Note on Least Squares Fitting of Functions Constrained to be Either Nonnegative, Nondecreasing or Convex

DOI10.1287/mnsc.20.1.130zbMath0305.90042OpenAlexW1989770444MaRDI QIDQ4062198

Warren T. Dent

Publication date: 1973

Published in: Management Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1287/mnsc.20.1.130

Mathematics Subject Classification ID

Convex programming (90C25) Quadratic programming (90C20)

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Fundamentals of cone regression ⋮ An O(n) algorithm for least squares quasi-convex approximation ⋮ Testing for and against a concavity restriction with normal errors ⋮ A direct algorithm for optimal quadratic splines ⋮ Concave regression: value-constrained estimation and likelihood ratio-based inference ⋮ Shape constrained smoothing using smoothing splines ⋮ Estimating nonparametric convex functions using gradient data

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