Slope heuristics: overview and implementation
نویسندگان
چکیده
منابع مشابه
Slope heuristics: overview and implementation
Model selection is a general paradigm which includes many statistical problems. One of the most fruitful and popular approaches to carry it out is the minimization of a penalized criterion. Birgé and Massart (2006) have proposed a promising data-driven method to calibrate such criteria whose penalties are known up to a multiplicative factor: the “slope heuristics”. Theoretical works validate th...
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Specific Gaussian mixtures are considered to solve simultaneously variable selection and clustering problems. A penalized likelihood criterion is proposed in Maugis and Michel (2008) to choose the number of mixture components and the relevant variable subset. This criterion is depending on unknown constants to be approximated in practical situations. A “slope heuristics” method is proposed and ...
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ژورنال
عنوان ژورنال: Statistics and Computing
سال: 2011
ISSN: 0960-3174,1573-1375
DOI: 10.1007/s11222-011-9236-1