ROBUST ORTHOGONAL REGRESSION FOR THE OUTLIER DETECTION WHEN COMPARING2 SERIES OF MEASUREMENT RESULTS

The application of a robust orthogonal regression procedure is describ ed for the outlier detection during the evaluation of a method compari son study and, in general, when comparing two series of measurement re sults. The procedure is based on the least median of the squared ortho gonal residuals (orthogonal LMS). It is concluded that the orthogonal LMS procedure is a useful screening tool to detect outlying values in a data set. Especially for data sets with extreme Values it is recomme nded to combine the robust data evaluation with a visual display. For the comparison of heteroscedastic methods, the program can easily be a dapted to a weighted orthogonal LMS variant.