Dependent Variable: Y Method: Least Squares Date: 05/23/00 Time: 05:55 Sample: 1 33 Included observations: 33 Variable Coefficient Std. Error t-Statistic Prob. C 102192.4 12799.83 7.983891 0.0000 N -9074.674 2052.674 -4.420904 0.0001 P 0.354668 0.072681 4.879810 0.0000 I 1.287923 0.543294 2.370584 0.0246 R-squared 0.618154 Mean dependent var 125634.6 Adjusted R-squared 0.578653 S.D. dependent v...

Pixel unmixing is commonly performed by employing a least squared (LS) error criterion, making it sensitive to outliers. As an alternative, the least median of squares (LMedS) method is proposed. Not only is it extremely robust, but it is efficient and straightforward both to implement and use.