LEAST TRIMMED SQUARES: NUISANCE PARAMETER FREE ASYMPTOTICS
Nielsen, Bent
The Least Trimmed Squares (LTS) regression estimator is known to be very robust to the presence of “outliers”. It is based on a clear and intuitive idea: in a sample of size n , it searches for the h -subsample of observations with the smallest sum of squared residuals. The remaining observations are declared “outliers”. Fast algorithms for its computation exist. Nevertheless, the existing asymptotic theory for LTS, based on the traditional -contamination model, shows that the asymptotic behavio