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Technical Note—On the Estimation of Convex Functions

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  • Charles A. Holloway

    (Stanford University, Stanford, California)

Abstract

We consider the estimation of a convex or concave relationship from a set of limited observations without prior specification of a functional form. A concave programming problem is shown to provide a “best” estimate for an arbitrary norm and n independent variables. The problem is shown to be well suited to a solution using the computational strategy of relaxation (a variant of generalized programming). An example illustrates the procedure and demonstrates the relationship to a procedure for n = 1 suggested by Dent.

Suggested Citation

  • Charles A. Holloway, 1979. "Technical Note—On the Estimation of Convex Functions," Operations Research, INFORMS, vol. 27(2), pages 401-407, April.
    • Handle: RePEc:inm:oropre:v:27:y:1979:i:2:p:401-407
    DOI: 10.1287/opre.27.2.401
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    Cited by:

    1. Kuosmanen, Timo & Johnson, Andrew, 2017. "Modeling joint production of multiple outputs in StoNED: Directional distance function approach," European Journal of Operational Research, Elsevier, vol. 262(2), pages 792-801.

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