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Approximating Linear Programs with Summary Functions: Pseudodata with an Infinite Sample

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  • Paul V. Preckel
  • Thomas W. Hertel

Abstract

A new algorithm for summarizing linear program models that takes advantage of the nature of linear program responses is presented. This method is equivalent to the pseudodata method based on an infinite sample. The power of the new method lies in the fact that the sampling procedure is sequential; the location of the next sample point is determined by observations at previous sample points. An illustration is provided, and the proposed method is compared with pseudodata based on out-of-sample predictions. The comparison indicates the new method is a distinct improvement.

Suggested Citation

  • Paul V. Preckel & Thomas W. Hertel, 1988. "Approximating Linear Programs with Summary Functions: Pseudodata with an Infinite Sample," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 70(2), pages 397-402.
    • Handle: RePEc:oup:ajagec:v:70:y:1988:i:2:p:397-402.
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    File URL: http://hdl.handle.net/10.2307/1242081
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    Cited by:

    1. Kristiaan Kerstens & Ignace Van de Woestyne, 2021. "Cost functions are nonconvex in the outputs when the technology is nonconvex: convexification is not harmless," Annals of Operations Research, Springer, vol. 305(1), pages 81-106, October.

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