Least-angle regression[6] is an estimation procedure for linear regression models that was developed to handle high-dimensional covariate vectors, potentially with more covariates than observations. The Theil–Sen estimator is a simple robust estimation technique that chooses the slope of the fit line to be the median of the slopes of the lines through pairs of sample points. It has similar statistical efficiency properties to simple linear regression but is much less sensitive to outliers.[19] Other robust estimation techniques, including the α-trimmed mean approach[citation needed], and L-, M-, S-, and R-estimators have been introduced.[citation needed]