In the classical leave-one-out procedure for outlier detection in regression analysis, we exclude an observation and then construct a model on remaining data. If difference between predicted observed value is high declare this outlier. As rule, those procedures utilize single comparison testing. The problem becomes much harder when observations can be associated with given degree of membership ...

Abstrart-Many practical applications of control system design based on input-output measurements permit the repeated application of a system identification procedure operating on closed-loop data together with successive refinements of the designed controller. Here we develop a paradigm for such an iterative design. The key to the procedure is to account for evaluated modelling error in the con...

For many least-squares decomposition models efficient algorithms are well known. A more difficult problem arises in decomposition models where each residual is weighted by a nonnegative value. A special case is principal components analysis with missing data. Kiers (1997) discusses an algorithm for minimizing weighted decomposition models by iterative majorization. In this paper, we propose a m...