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Identification and Preliminary Estimation in Linear Transfer Function Models
Scandinavian Journal of Statistics
Vol. 13, No. 4 (1986), pp. 239-255
Published by: Wiley on behalf of Board of the Foundation of the Scandinavian Journal of Statistics
Stable URL: http://www.jstor.org/stable/4616033
Page Count: 17
You can always find the topics here!Topics: Transfer functions, Statism, Spectral energy distribution, Estimation methods, Autoregressive moving average, Autocorrelation, Density estimation, Parametric models, Estimators, Economic models
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A new method based on spectral estimation is proposed for the identification and estimation of univariate ARMA-models. The method maximizes the entropy of the estimated innovation spectrum. On the other hand, it is possible to estimate the spectral density of the disturbance of a linear transfer function model without making any assumptions about the transfer function forms. This enables one to start the identification of a transfer function model by first estimating an ARMA-model for the disturbance. At the next stage, one can derive asymptotically efficient estimates for all the linear parameters in the model. On the basis of these efficient estimates, the specification of suitable transfer function forms is relatively straightforward.
Scandinavian Journal of Statistics © 1986 Board of the Foundation of the Scandinavian Journal of Statistics