[R] predict.arima

2007-09-08 Thread shao ran

Hi *,

Firstly, thank you so much for your time to read my email.

I am currently interested in how to use R to predict time series from
models fitted by ARIMA. The package I used is basic stats package, and the
method I used is predict.Arima.

What I know is that ARIMA parameters are estimated by Kalman Filter, but I
have difficulty in understanding how exactly maximum likelihood (ML)
estimator can be computed based on Kalman Filter, i.e. given a time series
and an ARIMA model, how can I compute the ARIMA parameters for prediction.

Could you please give me some help or provide some materials for it?

Thank you so much!


will

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[R] predict.Arima question

2006-10-19 Thread Felipe Santos
Hi,

I am trying to forecast a model using predict.Arima

I found arima model for a data set: x={x1,x2,x3,...,x(t)}

arima_model = arima(x,order=c(1,0,1))

I am forecasting the next N lags using predict:

arima_pred = predict(arima_model,n.ahead = N, se.fit=T)

If I have one more point in my series, let's say x(t+1). I do not want to
recalibrate themodel, I just want to forecast the next N-1 lags  using the
same model for x={x1,x2,...x(t)} but without recalibrate arima.

How to do it using arima + predict.Arima ?

My problem is that I am trying to fit arima models by brute force ( trying
lots of combinations for p and q and chosing the best model by AIC and BIC )
I have a big time series and I am running calibration for some sub-sequence
and I trying to forecast some points. I repeat this process for the next
contiguous subsequence and try to forecast again, until the big series end.

Thanks
Felipe

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Re: [R] predict.Arima question

2006-10-19 Thread Prof Brian Ripley
On Thu, 19 Oct 2006, Felipe Santos wrote:

 Hi,

 I am trying to forecast a model using predict.Arima

 I found arima model for a data set: x={x1,x2,x3,...,x(t)}

 arima_model = arima(x,order=c(1,0,1))

 I am forecasting the next N lags using predict:

 arima_pred = predict(arima_model,n.ahead = N, se.fit=T)

 If I have one more point in my series, let's say x(t+1). I do not want to
 recalibrate themodel, I just want to forecast the next N-1 lags  using the
 same model for x={x1,x2,...x(t)} but without recalibrate arima.

 How to do it using arima + predict.Arima ?

The short answer is that you cannot.  However, these are built on top of a 
Kalman filter implementation, and you could use the underlying C code.
It would be easier to make use of a modification of predict.arima0, 
though.

[...]

-- 
Brian D. Ripley,  [EMAIL PROTECTED]
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel:  +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UKFax:  +44 1865 272595

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