arma: Estimate ARMA model coefficients using maximum likelihood

In itsmr: Time Series Analysis Using the Innovations Algorithm

Estimate ARMA model coefficients using maximum likelihood

Description

Estimate ARMA model coefficients using maximum likelihood

Usage

arma(x, p = 0, q = 0)

Arguments

x	Time series data
p	AR order
q	MA order

Details

Calls the standard R function arima to estimate AR and MA coefficients. 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

autofit burg hannan ia yw

Examples

M = c("diff",1)
e = Resid(dowj,M)
a = arma(e,1,0)
print(a)

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