Multiresolution Nonparametric Intensity and Density Estimation

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dc.citation.bibtexNameinproceedingsen_US
dc.citation.conferenceNameIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)en_US
dc.contributor.authorWillett, Rebeccaen_US
dc.contributor.authorNowak, Robert Daviden_US
dc.contributor.orgDigital Signal Processing (http://dsp.rice.edu/)en_US
dc.date.accessioned2007-10-31T01:09:49Z
dc.date.available2007-10-31T01:09:49Z
dc.date.issued2002-05-20en
dc.date.modified2001-11-26en_US
dc.date.note2001-11-26en_US
dc.date.submitted2002-05-20en_US
dc.descriptionConference Paperen_US
dc.description.abstractThis paper introduces a new multiscale method for nonparametric piecewise polynomial intensity and density estimation of point processes. Fast, piecewise polynomial, maximum penalized likelihood methods for intensity and density estimation are developed. The recursive partitioning scheme underlying these methods is based on multiscale likelihood factorizations which, unlike conventional wavelet decompositions, are very well suited to applications with point process data. Experimental results demonstrate that multiscale methods can outperform wavelet and kernel based density estimation methods.en_US
dc.description.sponsorshipOffice of Naval Researchen_US
dc.description.sponsorshipArmy Research Officeen_US
dc.description.sponsorshipNational Science Foundationen_US
dc.identifier.citationR. Willett and R. D. Nowak, "Multiresolution Nonparametric Intensity and Density Estimation," 2002.
dc.identifier.doihttp://dx.doi.org/10.1109/ICASSP.2002.5744896en_US
dc.identifier.urihttps://hdl.handle.net/1911/20448
dc.language.isoeng
dc.subjectPoisson*
dc.subjectmultiscale*
dc.subjectkernel*
dc.subjectwavelet*
dc.subjectpolynomial*
dc.subject.keywordPoissonen_US
dc.subject.keywordmultiscaleen_US
dc.subject.keywordkernelen_US
dc.subject.keywordwaveleten_US
dc.subject.keywordpolynomialen_US
dc.titleMultiresolution Nonparametric Intensity and Density Estimationen_US
dc.typeConference paper
dc.type.dcmiText
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