autofit: Find the best model from a range of possible ARMA models

In itsmr: Time Series Analysis Using the Innovations Algorithm

Find the best model from a range of possible ARMA models

Description

Find the best model from a range of possible ARMA models

Usage

autofit(x, p = 0:5, q = 0:5)

Arguments

x	Time series data (typically residuals from Resid)
p	Range of AR orders
q	Range of MA orders

Details

Tries all combinations of p and q and returns the model with the lowest AICC. The arguments p and q should be small ranges as this function can be slow otherwise. The innovations algorithm is used to estimate white noise variance.

Value

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

See Also

arma

Examples

M = c("diff",1)
e = Resid(dowj,M)
a = autofit(e)
print(a)

itsmr documentation built on Aug. 6, 2022, 9:08 a.m.