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Exact Calculation of Normalized Maximum Likelihood Code Length Using Fourier Analysis

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arxiv 1801.03705 v1 pith:XBGXSERM submitted 2018-01-11 math.ST stat.TH

Atsushi Suzuki , Kenji Yamanishi This is my paper · ORCID
classification math.STstat.TH
keywords calculationcodelengthlikelihoodmaximumnormalizedanalysisbeen
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The normalized maximum likelihood code length has been widely used in model selection, and its favorable properties, such as its consistency and the upper bound of its statistical risk, have been demonstrated. This paper proposes a novel methodology for calculating the normalized maximum likelihood code length on the basis of Fourier analysis. Our methodology provides an efficient non-asymptotic calculation formula for exponential family models and an asymptotic calculation formula for general parametric models with a weaker assumption compared to that in previous work.

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  1. Minimum Description Length Revisited

    stat.ME 2019-08 accept novelty 3.0 of 10

    Minimum Description Length is presented as a general framework that subsumes penalized likelihood and Bayesian model selection, with luckiness functions replacing priors and worst-case regret replacing average risk.

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