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For some time it has been well known among specialists in mathematical programming that the statistical problem of fitting a linear multiple regression with the criterion of minimizing the sum of absolute deviations from the regression function (rather than squared deviations) may be reduced to a linear programming problem. But this knowledge seems not widespread among general statisticians.1 This note briefly reviews the formulation of this application of linear programming, and its history.
Walter D. Fisher (Thu,) studied this question.