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A Multivariate Approach to Time Series Forecasting of Copper Prices with the Help of Multiple Imputation by Chained Equations and Multivariate Adaptive Regression Splines

dc.contributor.authorSánchez Lasheras, Fernando 
dc.contributor.authorGracia Rodríguez, Javier 
dc.contributor.authorGarcía Nieto, Paulino José 
dc.contributor.authorGarcía Gonzalo, María Esperanza 
dc.contributor.authorFidalgo Valverde, Gregorio 
dc.date.accessioned2021-06-01T09:44:49Z
dc.date.available2021-06-01T09:44:49Z
dc.date.issued2021
dc.identifier.isbn9783030578015
dc.identifier.issn2194-5357
dc.identifier.urihttp://hdl.handle.net/10651/58961
dc.descriptionInternational Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO) (15th. 2020. Burgos, Spain)
dc.format.extentp. 691-701
dc.language.isoeng
dc.relation.ispartof15th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2020)
dc.relation.ispartofseriesAdvances in Intelligent Systems and Computing; 1268
dc.rights© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021
dc.sourceScopus
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85091277162&doi=10.1007%2f978-3-030-57802-2_66&partnerID=40&md5=74fddb53b9dad7e36a016dbdc6ba6730
dc.titleA Multivariate Approach to Time Series Forecasting of Copper Prices with the Help of Multiple Imputation by Chained Equations and Multivariate Adaptive Regression Splines
dc.typeinfo:eu-repo/semantics/conferenceObject
dc.identifier.doi10.1007/978-3-030-57802-2_66
dc.type.dcmitext
dc.relation.publisherversionhttp://dx.doi.org/10.1007/978-3-030-57802-2_66


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