Again, consider the linear zero-mean ARMA(p, p) model of question 1. Let yt|h = E(yt y1,

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Again, consider the linear zero-mean ARMA(p, p) model of question 1.

Let yt|h = E(yt ∣ y1, y2,…, yh) be the conditional expectation of yt given Fh = ????{y1,…, yh}, where h ≤ t. Let xt = (yt|t, yt+1|t,…, yt+p−1|t)′ be a pdimensional state vector. Derive an SSM for yt using the state variable xt.

This state space representation of ARMA models was proposed by Akaike

(1975).

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Nonlinear Time Series Analysis

ISBN: 9781119264057

1st Edition

Authors: Ruey S. Tsay, Rong Chen

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Question Posted: Jun 06, 2024 01:09 AM

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Again, consider the linear zero-mean ARMA(p, p) model of question 1. Let yt|h = E(yt y1,

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Nonlinear Time Series Analysis

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