hannan | R Documentation |
Estimate ARMA coefficients using the Hannan-Rissanen algorithm
hannan(x, p, q)
x |
Time series data (typically residuals from |
p |
AR order |
q |
MA order ( |
The innovations algorithm is used to estimate white noise variance.
Returns an ARMA model consisting of a list with the following components.
phi |
Vector of AR coefficients (index number equals coefficient subscript) |
theta |
Vector of MA coefficients (index number equals coefficient subscript) |
sigma2 |
White noise variance |
aicc |
Akaike information criterion corrected |
se.phi |
Standard errors for the AR coefficients |
se.theta |
Standard errors for the MA coefficients |
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M = c("diff",12) e = Resid(deaths,M) a = hannan(e,1,1) print(a)
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