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Advances in Intelligent and Soft Computing
The focus is on robust regression methods for problems where the predictor matrix has full rank and where it is rank deficient. For the first situation, various robust regression methods have been introduced, and here an overview of the most important proposals is given. For the latter case, robust partial least squares regression is discussed. The way of downweighting outlying observations is important. Using continuous weights (leading to "soft" robust methods) has advantages over 0/1 weightsdoi:10.1007/978-3-642-14746-3_34 dblp:conf/smps/Filzmoser10 fatcat:xzafhlddsfcndbxfkmr33z34oi