arima() function, one can specify a list of covariates while estimating the AR and MA coefficients using the
xreg argument. For instance:
arima(lh, c(2,0,1), xreg= 1:length(lh))
returns a model with ARMA(2,0) disturbance and the linear effect of time series
Call: arima(x = lh, order = c(2, 0, 1), xreg = 1:length(lh)) Coefficients: ar1 ar2 ma1 intercept 1:length(lh) 1.3957 -0.6453 -1.0000 2.1072 0.0105 s.e. 0.1065 0.1082 0.0589 0.0585 0.0023 sigma^2 estimated as 0.1411: log likelihood = -22.85, aic = 57.7
Is there any equivalent method in R when fitting an ARFIMA (Autoregressive fractionally integrated moving average) model? I know it is possible to run a multiple regression on the residuals of an ARFIMA model, but this is different from estimating them together and would like to learn if anyone has a better suggestion.