Forecasting with missing data: Application to a real case

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• dc.contributor.author Delicado, Pedroca
• dc.contributor.author Justel, Anaca
• dc.contributor.other Universitat Pompeu Fabra. Departament d'Economia i Empresa
• dc.date.accessioned 2017-07-26T12:08:01Z
• dc.date.available 2017-07-26T12:08:01Z
• dc.date.issued 1997-05-01
• dc.date.modified 2017-07-23T02:02:59Z
• dc.description.abstract This paper presents a comparative analysis of linear and mixed models for short term forecasting of a real data series with a high percentage of missing data. Data are the series of significant wave heights registered at regular periods of three hours by a buoy placed in the Bay of Biscay. The series is interpolated with a linear predictor which minimizes the forecast mean square error. The linear models are seasonal ARIMA models and the mixed models have a linear component and a non linear seasonal component. The non linear component is estimated by a non parametric regression of data versus time. Short term forecasts, no more than two days ahead, are of interest because they can be used by the port authorities to notice the fleet. Several models are fitted and compared by their forecasting behavior.
• dc.format.mimetype application/pdfca
• dc.identifier https://econ-papers.upf.edu/ca/paper.php?id=213
• dc.identifier.citation Journal of Forecasting, 18, 285-298, 1999
• dc.identifier.uri http://hdl.handle.net/10230/795
• dc.language.iso eng
• dc.relation.ispartofseries Economics and Business Working Papers Series; 213
• dc.rights L'accés als continguts d'aquest document queda condicionat a l'acceptació de les condicions d'ús establertes per la següent llicència Creative Commons
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/es/
• dc.subject.keyword significant wave height
• dc.subject.keyword mean square error
• dc.subject.keyword linear interpolation
• dc.subject.keyword arima models
• dc.subject.keyword nonparametric smoothing
• dc.subject.keyword Statistics, Econometrics and Quantitative Methods
• dc.title Forecasting with missing data: Application to a real caseca
• dc.title.alternative Forecasting with missing data: Application to coastal wave heights
• dc.type info:eu-repo/semantics/workingPaper