Constrained Maximum Likelihood

Ronald Schoenberg ()

Computational Economics, 1997, vol. 10, issue 3, 66 pages

Abstract: Constrained Maximum Likelihood (CML), developed at Aptech Systems, generates maximum likelihood estimates with general parametric constraints (linear or nonlinear, equality or inequality), using the sequential quadratic programming method. CML computes two classes of confidence intervals by inversion of the Wald and likelihood ratio statistics, and by simulation. The inversion techniques can produce misleading test sizes, but Monte Carlo evidence suggests this problem can be corrected under certain circumstances. Citation Copyright 1997 by Kluwer Academic Publishers.

Date: 1997
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