Maximum Likelihood Transfer Function Modelling

P. J. Brockwell, R. A. Davis and H. Salehi
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P. J. Brockwell: Colorado State University, Department of Statistics
R. A. Davis: Colorado State University, Department of Statistics
H. Salehi: Michigan State University, Department of Probability and Statistics

A chapter in Computing Science and Statistics, 1992, pp 303-306 from Springer

Abstract: Abstract A state-space realization of the transfer-function model of Box and Jenkins (1976) is used to compute the exact Gaussian likelihood of the stationary input-output series, (X t’ Y t),t = 1,…,n, and to compute the exact linear mean-square predictor of the output Y t+h based on (X t’ Y t),t = 1,…,n. We show how to use the state-space formulation for model selection with the A1C criterion and for the analysis of data with missing values in either or both of the input and output series. An extension of the argument (discussed elsewhere) can also be used for the analysis of transfer function models with non-stationary input and output sequences. The results are illustrated with reference to the Leading Indicator — Sales Data of Box and Jenkins.

Keywords: Power Series Expansion; Sales Data; Output Series; Leading Indicator; Maximum Likelihood Estima (search for similar items in EconPapers)
Date: 1992
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4612-2856-1_41

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DOI: 10.1007/978-1-4612-2856-1_41

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