Projection pursuit for discrete data

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dc.creatorDiaconis, Persi
dc.creatorSalzman, Julia
dc.date2008-05-20
dc.date.accessioned2026-07-07T12:19:05Z
dc.date.available2026-07-07T12:19:05Z
dc.descriptionThis paper develops projection pursuit for discrete data using the discrete Radon transform. Discrete projection pursuit is presented as an exploratory method for finding informative low dimensional views of data such as binary vectors, rankings, phylogenetic trees or graphs. We show that for most data sets, most projections are close to uniform. Thus, informative summaries are ones deviating from uniformity. Syllabic data from several of Plato's great works is used to illustrate the methods. Along with some basic distribution theory, an automated procedure for computing informative projections is introduced.
dc.descriptionPublished in at http://dx.doi.org/10.1214/193940307000000482 the IMS Collections (http://www.imstat.org/publications/imscollections.htm) by the Institute of Mathematical Statistics (http://www.imstat.org)
dc.identifierhttps://arxiv.org/abs/0805.3043
dc.identifierhttp://arxiv.org/abs/0805.3043
dc.identifierIMS Collections 2008, Vol. 2, 265-288
dc.identifierdoi:10.1214/193940307000000482
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/212630
dc.subjectStatistics Theory
dc.subjectApplications
dc.subjectMethodology
dc.subject44A12, 62K10, 90C08 (Primary)
dc.titleProjection pursuit for discrete data
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