Authors: Gather, Ursula
Mildenberger, Thoralf
Rozenholc, Yves
Title: Constructing irregular histograms by penalized likelihood
Language (ISO): en
Abstract: We propose a fully automatic procedure for the construction of irregular histograms. For a given number of bins, the maximum likelihood histogram is known to be the result of a dynamic programming algorithm. To choose the number of bins, we propose two different penalties motivated by recent work in model selection by Castellan [1] and Massart [2]. We give a complete description of the algorithm and a proper tuning of the penalties. Finally, we compare our procedure to other existing proposals for a wide range of different densities and sample sizes. [1] Castellan, G., 1999. Modified Akaike's criterion for histogram density estimation. Technical Report 99.61, Universit√© de Paris-Sud. [2] Massart, P., 2007. Concentration inequalities and model selection. Lecture Notes in Mathematics Vol. 1896, Springer, New York.
Subject Headings: density estimation
dynamic programming
irregular histogram
penalized likelihood
Issue Date: 2009-04-30T10:42:23Z
Appears in Collections:Sonderforschungsbereich (SFB) 475

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