Model selection and sensitivity analysis for sequence pattern models

dc.creatorGupta, Mayetri
dc.date2008-05-16
dc.date.accessioned2026-07-07T12:18:59Z
dc.date.available2026-07-07T12:18:59Z
dc.descriptionIn this article we propose a maximal a posteriori (MAP) criterion for model selection in the motif discovery problem and investigate conditions under which the MAP asymptotically gives a correct prediction of model size. We also investigate robustness of the MAP to prior specification and provide guidelines for choosing prior hyper-parameters for motif models based on sensitivity considerations.
dc.descriptionPublished in at http://dx.doi.org/10.1214/193940307000000301 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/0805.2523
dc.identifierhttp://arxiv.org/abs/0805.2523
dc.identifierIMS Collections 2008, Vol. 1, 390-407
dc.identifierdoi:10.1214/193940307000000301
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/212598
dc.subjectStatistics Theory
dc.subjectMethodology
dc.subject62F15, 62P10 (Primary) 62F12 (Secondary)
dc.titleModel selection and sensitivity analysis for sequence pattern models
dc.typetext

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