Title: Multi-step-ahead estimation of time series models
Authors : McElroy, Tucker
Wildi, Marc
Published in : International Journal of Forecasting
Volume(Issue) : 29
Issue : 3
Pages : 378
Pages to: 394
Publisher / Ed. Institution : Elsevier
Issue Date: 2013
License (according to publishing contract) : Licence according to publishing contract
Type of review: Peer review (publication)
Language : English
Subject (DDC) : 003: Systems
500: Natural sciences and mathematics
Abstract: We study the fitting of time series models via the minimization of a multi-step-ahead forecast error criterion that is based on the asymptotic average of squared forecast errors. Our objective function uses frequency domain concepts, but is formulated in the time domain, and allows the estimation of all linear processes (e.g., ARIMA and component ARIMA). By using an asymptotic form of the forecast mean squared error, we obtain a well-defined nonlinear function of the parameters that is proven to be minimized at the true parameter vector when the model is correctly specified. We derive the statistical properties of the parameter estimates, and study the asymptotic impact of model misspecification on multi-step-ahead forecasting. The method is illustrated through a forecasting exercise, applied to several time series.
Departement: School of Engineering
Organisational Unit: Institute of Data Analysis and Process Design (IDP)
Publication type: Article in scientific journal
DOI : 10.1016/j.ijforecast.2012.08.003
ISSN: 0169-2070
URI: https://digitalcollection.zhaw.ch/handle/11475/13640
Appears in Collections:Publikationen School of Engineering

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