On high breakdown point estimation
The linear regression model \(Y_i=\sum_{j=1}^pX_{ij}\beta_j+e_i\), \(i=1,2,...\), is considered. The aim of paper is to clarify the behaviour of high breakdown point estimators for this model. The performance of new algorithms for the least median of squares and the least trimmed squares is discussed. Some numerical examples are considered and it is shown that some caution is inevitable.
scientific article; zbMATH DE number 1409717