Usually, in the Theory of Optimal Experimental Design the model is assumed to be known at the design stage. In practice, however, more competing models may be plausible for the same data. Thus, a possibility is to find an optimal design which take both model discrimination and parameter...

The KL-optimality criterion has been recently proposed to discriminate between any two statistical models. However, designs which are optimal for model discrimination may be inadequate for parameter estimation. In this paper, the DKL-optimality criterion is proposed which is useful for the dual...

Analysis of the E-Learning survey at University of Milan. In this work we use several statistical techniques to studythe data from a survey on the faculty staff of the University of Milan on E-Learning practices. In particularly, the analysis wasfocused on the identification of typical profiles...