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Accession Number PB2012-114725
Title Multi-Step Ahead Estimation of Time Series Models.
Publication Date Sep 2012
Media Count 37p
Personal Author M. Wildi T. McElroy
Abstract We study the fitting of time series models via 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 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 provably 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.
Keywords Estimates
Forecasting
Mathematical models
Parameters
Statistical data
Time domain
Time series analysis

 
Source Agency Department of Commerce, Bureau of Census
NTIS Subject Category 72B - Algebra, Analysis, Geometry, & Mathematical Logic
Corporate Author Bureau of the Census, Washington, DC. Center for Statistical Research and Methodology.
Document Type Technical report
Title Note N/A
NTIS Issue Number 1226
Contract Number N/A

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