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This paper discusses whether differences in the data structure of observational and experimental studies should lead to different strategies for variable selection. On the one hand, it is argued that outliers in the predictor variables have to be treated differently in the two kinds of studies....
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We propose a new information theoretically based optimization criterion for the estimation of mixture density models and compare it with other methods based on maximum likelihood and maximum a posterio estimation. For the optimization, we employ an evolutionary algorithm which estimates both...
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We describe a computer intensive method for linear dimension reduction which minimizes the classification error directly. Simulated annealing Bohachevsky et al (1986) is used to solve this problem. The classification error is determined by an exact integration. We avoid distance or scatter...
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