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Forecasting binary longitudinal data by a functional PC-ARIMA model

dc.contributor.authorAguilera Del Pino, Ana María 
dc.contributor.authorEscabias Machuca, Manuel 
dc.contributor.authorValderrama Bonnet, Mariano José 
dc.date.accessioned2022-02-24T09:31:44Z
dc.date.available2022-02-24T09:31:44Z
dc.date.issued2008-02-20
dc.identifier.citationAna M. Aguilera, Manuel Escabias, Mariano J. Valderrama, Forecasting binary longitudinal data by a functional PC-ARIMA model, Computational Statistics & Data Analysis, Volume 52, Issue 6, 2008, Pages 3187-3197, ISSN 0167-9473, https://doi.org/10.1016/j.csda.2007.09.015es_ES
dc.identifier.urihttp://hdl.handle.net/10481/72990
dc.description.abstractIn order to forecast time evolution of a binary response variable from a related continuous time series a functional logit model is proposed. The estimation of this model from discrete time observations of the predictor is solved by using functional principal component analysis and ARIMA modelling of the associated discrete time series of principal components. The proposed model is applied to forecast the risk of drought from El Niño phenomenon.es_ES
dc.description.sponsorshipProjects MTM2007-63793 from Dirección General de Investigación, Ministerio de Educación y Ciencia, Spain and P06-FQM-01470 from Consejería de Innovación Ciencia y Empresa, Junta de Andalucía, Spaines_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.rightsAtribución-SinDerivadas 3.0 España*
dc.rights.urihttp://creativecommons.org/licenses/by-nd/3.0/es/*
dc.subjectLogistic regressiones_ES
dc.subjectFunctional principal component analysises_ES
dc.subjectARIMA modellinges_ES
dc.titleForecasting binary longitudinal data by a functional PC-ARIMA modeles_ES
dc.typejournal articlees_ES
dc.rights.accessRightsembargoed accesses_ES
dc.identifier.doihttps://doi.org/10.1016/j.csda.2007.09.015
dc.type.hasVersionSMURes_ES


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