Titlebook: Maximum Penalized Likelihood Estimation; Volume I: Density Es P. P. B. Eggermont,V. N. LaRiccia Book 2001 Springer Science+Business Media,

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P. P. B. Eggermont,V. N. LaRicciats s- ported both by the European Commission and Czech grant bodies. The source text has served as a common basis of communication for the research team. When accumulating and re?ning the material we found that the text could also serve as ? a grand example of the strength of dynamic Bayesian decisi

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P. P. B. Eggermont,V. N. LaRicciaynamic decision making under uncertainty in a complex enviroThis work summarizes the theoretical and algorithmic basis of optimized pr- abilistic advising. It developed from a series of targeted research projects s- ported both by the European Commission and Czech grant bodies. The source text has s

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ts s- ported both by the European Commission and Czech grant bodies. The source text has served as a common basis of communication for the research team. When accumulating and re?ning the material we found that the text could also serve as ? a grand example of the strength of dynamic Bayesian decisi

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lly the German University "the unity of research and teaching" (Humboldt) is far from dead and can be updated any time, provided a suited research project. Our special thanks go to J?rn Schmidt from the former Center for Interdisciplinary Research in Higher Education at our University, whose constan

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P. P. B. Eggermont,V. N. LaRiccially the German University "the unity of research and teaching" (Humboldt) is far from dead and can be updated any time, provided a suited research project. Our special thanks go to J?rn Schmidt from the former Center for Interdisciplinary Research in Higher Education at our University, whose constan

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