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Autoregressive Models: The Yule-Walker Equations

February 8, 2019 by 3200 Creative

Autoregressive models for time series are widely used because of their simplicity and their applicability to resonant phenomena. In this lesson you will learn how the Yule-Walker equations relate the autoregressive model parameters to the autocovariance of the time series. The autoregressive model parameters are obtained from the autocovariance of the time series by solving a system of linear equations. The Yule-Walker equations provide a straightforward means to estimate an autoregressive model from data.

Prerequisites

  • LTI System Models for Random Signals

Key Concepts and Screenshots

Concepts and Screenshots for Autoregressive Models: The Yule-Walker Equations

Supplementary Material

  • m-file: Autoregressive Models - The Yule-Walker Equations
QuizzesStatus
1

Autoregressive Models The Yule Walker Equations


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  • Introduction to Random Signal Representations

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  • Random Processes and Stationarity

  • The Power Spectral Density

  • Cross Spectra and Coherence

  • LTI System Models for Random Signals

  • Autoregressive Models: The Yule-Walker Equations

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  • Random Signal Characterization

  • Basis Representations of Signals

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