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Estimate MA coefficients using the innovations algorithm
ia(x, q, m = 17)
Returns an ARMA model consisting of a list with the following components.
0
Vector of MA coefficients (index number equals coefficient subscript)
White noise variance
Akaike information criterion corrected
Standard errors for the MA coefficients
Time series data (typically residuals from Resid)
Resid
MA order
Recursion level
Normally m should be set to the default value. The innovations algorithm is used to estimate white noise variance.
m
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M = c("diff",1) e = Resid(dowj,M) a = ia(e,1) print(a)
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