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On the Uniqueness and Globality of Optimal Data Gathering Strategies

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  • Carlos F. Daganzo

    (University of California, Berkeley, California)

Abstract

It was shown in a previous publication that, in order to minimize the prediction error of a statistical model with a discrete dependent variable, it is possible to design an optimal survey by solving a nonlinear mathematical program with linear constraints. It is shown here that this mathematical program is a convex programming problem and that the gradient and Hessian of the objective function admit a closed form. Consequently, very efficient optimal seeking methods which guarantee a globally optimal sampling strategy can be used. As a byproduct of the analysis a simple test for multicollinearity was also developed.

Suggested Citation

  • Carlos F. Daganzo, 1982. "On the Uniqueness and Globality of Optimal Data Gathering Strategies," Transportation Science, INFORMS, vol. 16(2), pages 241-245, May.
    • Handle: RePEc:inm:ortrsc:v:16:y:1982:i:2:p:241-245
    DOI: 10.1287/trsc.16.2.241
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