[R] Manually reconstructing arima model from coefficients

[sergey777]

Colleagues

I am a new to R but already love it.

I have the following problem:
I fitted arima model to my time series like this (please ignore modeling
parameters as they are not important now):
x = scan("C:/data.txt") 
x = ts(x, start=1, frequency=1)
x.fit<-arima(x, order = c(1,0,0), seasonal = list(order=c(0,0,1)))
 
Now I want to use this model for forecasting and backtesting (!). My goal is
to apply exactly this model to different data – another time series object,
let’s call it “y”. How can I do this in R.

One of the options is to extract coefficients and to create my own function
that can be applied to any time series but I suspect and hope that there is
a better way of doing this.
If there is not an easy option can anyone suggest a complete equation that
includes seasonal terms  that can be easily programmed (for example in C)
for a person who knows some programming but very little math.

Thank you. 


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