How to find coefficients of AR model using yule-walker equation?
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The Yule-Walker equations are used to find the coefficients of an autoregressive (AR) model. These equations relate the cross-covariances of a stationary VAR model with the matrices of the autoregressive coefficients and the covariance matrix of the noise . In the case of a nonlinear autoregressive model, higher order statistics are used instead of autocovariances, and the Yule-Walker equations are derived using a compact matrix notation . The Yule-Walker equations are a set of linear equations for the regression coefficients in terms of the autocorrelation functions . The estimation of AR parameters using the Yule-Walker equations involves solving the equations using methods like the Durbin-Levinson algorithm . The Yule-Walker equations can also be derived for nonlinear AR models within the framework of kernel machines, and solving these equations is shown to be relatively easy .
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23 Citations | The paper proposes using Yule-Walker equations to find the coefficients of the autoregressive (AR) model. |
| The Yule-Walker equations can be used to estimate the coefficients of an AR model by solving a set of equations involving the autocorrelation function coefficients. | |
| The Yule-Walker equations can be used to find the coefficients of an autoregressive (AR) model by estimating the autocorrelation functions. | |
| The Yule-Walker equations can be used to estimate the coefficients of an autoregressive (AR) model in multivariate time series analysis. | |
01 Sep 2019 4 Citations | The paper proposes using higher order statistics instead of autocovariances to derive Yule-Walker equations for the nonlinear autoregressive model. |
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