Goal Programming Approach for Regression Median*

In: Decision sciences, Band 20, Heft 4, S. 700-713

Abstract

ABSTRACTThis study presents a new robust estimation method that can produce a regression median hyper‐plane for any data set. The robust method starts with dual variables obtained by least absolute value estimation. It then utilizes two specially designed goal programming models to obtain regression median estimators that are less sensitive to a small sample size and a skewed error distribution than least absolute value estimators. The superiority of new robust estimators over least absolute value estimators is confirmed by two illustrative data sets and a Monte Carlo simulation study.