A copula-based method for synthetic microarray data generation

dc.contributor	Universitat de Vic. Escola Politècnica Superior
dc.contributor	Universitat de Vic. Grup de Recerca en Tecnologies Digitals
dc.contributor	International Conference on Advances in Statistics (2012: Barcelona)
dc.contributor.author	Lew, Sergio
dc.contributor.author	Solé-Casals, Jordi
dc.contributor.author	Caiafa, Cesar F.
dc.contributor.author	Bau i Macià, Josep
dc.date.accessioned	2014-04-07T12:21:31Z
dc.date.available	2014-04-07T12:21:31Z
dc.date.created	2012
dc.date.issued	2012
dc.identifier.uri	http://hdl.handle.net/10854/2858
dc.description.abstract	In this work, we propose a copula-based method to generate synthetic gene expression data that account for marginal and joint probability distributions features captured from real data. Our method allows us to implant significant genes in the synthetic dataset in a controlled manner, giving the possibility of testing new detection algorithms under more realistic environments.	en
dc.format	application/pdf
dc.format.extent	3 p.	ca_ES
dc.language.iso	eng	ca_ES
dc.rights	Aquest document està subjecte a aquesta llicència Creative Commons	ca_ES
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.other	Dependència (Estadística)	ca_ES
dc.subject.other	Distribució (Teoria de la probabilitat)	ca_ES
dc.title	A copula-based method for synthetic microarray data generation	en
dc.type	info:eu-repo/semantics/conferenceObject	ca_ES
dc.rights.accessRights	info:eu-repo/semantics/openAccess	ca_ES

Except where otherwise noted, this item's license is described as http://creativecommons.org/licenses/by-nc-nd/3.0/es/