# Software for fitting generalized least squares model with errors that follow seasonal ARMA model

I need to fit a GLS model, with some known regressors, and where the errors follow an unknown ${\rm ARIMA}(1,0,1) \times (1,N,1)$ model. It seems like the main tool out there for such models is the gls function in the nlme package for R.

In gls, one specifies the correct correlation struction using a corStruct object, but I cannot find any corStruct objects for specifying my (really simple) seasonal model. I am new to R, so I don't think I am up for coding a new corStruct for my purposes. Are there any other packages out there for solving this problem? If not, can you point me to some references about how to create custom corStruct objects. Thanks for all your help!

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@nbrent I have written such a piece of software. It is called AUTOBOX and is available from autobox.com. –  IrishStat Jun 10 '12 at 19:53

The arima() function in R will do what you want:

fit <- arima(y, xreg=x, order=c(1,0,1), seasonal=c(1,N,1))


where x is the matrix of regressors and y is the time series you wish to model.

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