Neykov, N.M.; Čížek, P.; Filzmoser, P.; Neytchev, P.N. - In: Computational Statistics & Data Analysis 56 (2012) 6, pp. 1757-1770
The linear quantile regression estimator is very popular and widely used. It is also well known that this estimator can be very sensitive to outliers in the explanatory variables. In order to overcome this disadvantage, the usage of the least trimmed quantile regression estimator is proposed to...
