The Fisher large-sample information matrix per observation for the p coefficients in an AR(p) is computed.
vector of length p corresponding to the AR(p) coefficients
The Fisher information matrix is computed as the covariance matrix
of an AR(p) process with coefficients given in the argument
phi and with unit innovation variance.
TacvfAR function is used to compute the necessary
InformationMatrixAR to obtain estimates
of the standard errors for the estimated parameters in the case
of the full AR(p) model.
a p-by-p Toeplitz matrix, p = length(phi)
A.I. McLeod and Y. Zhang
McLeod, A.I. and Zhang, Y. (2006). Partial autocorrelation parameterization for subset autoregression. Journal of Time Series Analysis, 27, 599-612.
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