Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/41047 
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dc.contributor.authorRozenholc, Yvesen
dc.contributor.authorMildenberger, Thoralfen
dc.contributor.authorGather, Ursulaen
dc.date.accessioned2009-09-02-
dc.date.accessioned2010-10-18T13:05:57Z-
dc.date.available2010-10-18T13:05:57Z-
dc.date.issued2009-
dc.identifier.urihttp://hdl.handle.net/10419/41047-
dc.description.abstractWe 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.en
dc.language.isoengen
dc.publisher|aTechnische Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen |cDortmunden
dc.relation.ispartofseries|aTechnical Report |x2009,04en
dc.subject.ddc519en
dc.subject.keywordirregular histogramen
dc.subject.keyworddensity estimationen
dc.subject.keywordpenalized likelihooden
dc.subject.keyworddynamic programmingen
dc.titleConstructing irregular histograms by penalized likelihood-
dc.typeWorking Paperen
dc.identifier.ppn60804363Xen
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen
dc.identifier.repecRePEc:zbw:sfb475:200904en

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