On the Uniqueness and Globality of Optimal Data Gathering Strategies

Carlos F. Daganzo
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Carlos F. Daganzo: University of California, Berkeley, California

Transportation Science, 1982, vol. 16, issue 2, 241-245

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.

Date: 1982
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Persistent link: https://EconPapers.repec.org/RePEc:inm:ortrsc:v:16:y:1982:i:2:p:241-245

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