A min-max algorithm for non-linear regression models

A. Tishler*, I. Zang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


We present a simple method for the nonlinear min-max (or L) estimation problem. The method consists of locally smoothing out the nondifferentiabilities in the original L problem, resulting in an approximate differentiable one that can be estimated using standard gradient techniques. The accuracy of the approximation is determined by a single parameter, whose choice determines a priori the length of the uncertainty interval in the maximal absolute error for the solution of the original L problem. In addition, we present some numerical examples demonstrating the efficiency of the method.

Original languageEnglish
Pages (from-to)95-115
Number of pages21
JournalApplied Mathematics and Computation
Issue number1-2
StatePublished - Aug 1983


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