An empirical study of minimum description length model selection with infinite parametric complexity
نویسندگان
چکیده
منابع مشابه
An Empirical Study of Minimum Description Length Model Selection with Infinite Parametric Complexity
Parametric complexity is a central concept in Minimum Description Length (MDL) model selection. In practice it often turns out to be infinite, even for quite simple models such as the Poisson and Geometric families. In such cases, MDL model selection as based on NML and Bayesian inference based on Jeffreys’ prior can not be used. Several ways to resolve this problem have been proposed. We condu...
متن کاملAn Empirical Study of MDL Model Selection with Infinite Parametric Complexity
Parametric complexity is a central concept in MDL model selection. In practice it often turns out to be infinite, even for quite simple models such as the Poisson and Geometric families. In such cases, MDL model selection as based on NML and Bayesian inference based on Jeffreys’ prior can not be used. Several ways to resolve this problem have been proposed. We conduct experiments to compare and...
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ژورنال
عنوان ژورنال: Journal of Mathematical Psychology
سال: 2006
ISSN: 0022-2496
DOI: 10.1016/j.jmp.2005.11.008