Arbeitspapier

Constructing irregular histograms by penalized likelihood

to related objects

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 [6] and Massart [26]. 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.

Language: Englisch

Bibliographic citation: Series: Technical Report ; No. 2009,04

Subject: irregular histogram
density estimation
penalized likelihood
dynamic programming

Event: Geistige Schöpfung

(who): Rozenholc, Yves
Mildenberger, Thoralf
Gather, Ursula

Event: Veröffentlichung

(who): Technische Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen

(where): Dortmund

(when): 2009

Handle: http://hdl.handle.net/10419/41047

Last update: 10.03.2025, 11:46 AM CET

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Object type

Arbeitspapier

Associated

Rozenholc, Yves
Mildenberger, Thoralf
Gather, Ursula
Technische Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen

Time of origin

2009

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