How do you propose to forecast? If it were me, I'd first worry about
what to use to model, then the forecasting. I'd start with normal
probability plots to make sure I didn't have any outliers, need a
transformation, etc. If all looked plausibly normally distributed, I
might first fit a linear regression model using "lm", then do
"acf" and
"pacf" of the residuals, select a time series model for the residuals,
and fit the full model using "arima". The output from
"arima" is a
list, one of whose components is "residuals", which are the one-step
ahead forecast errors. To compute the one-step ahead predictions, I
believe you just subtract those from the observations. However, there
is also a "predict" function that has an "arima" method, and
I would use
that to spot-check the numbers to make sure I understood.
Do you have Venables and Ripley (2000) Modern Applied Statistics with
S, 4th ed. (Springer)? If you aren't already familiar with the chapter
in that book on time series, I suggest you start there.
If you'd like further help from this group, I suggest you first
PLEASE do read the posting guide!
"www.R-project.org/posting-guide.html": Anectotal evidence suggests
that questions that follow more closely the recommendations in the
posting guide tend to get more useful answers quicker.
hope this helps.
spencer graves
Sumanta Basak wrote:
> Hi R-Users,
>
>
>
> I apologize if it is too simple question for all. I have a multivariate
> dataset having 7 variables as independent and 1 dependent variable. 248
> data points are there. I want to do out sample forecast first
> considering 156 points. So I'll have to start from 157th point and
> calculate the 157th y_hat value. In this way it will go to 248th data
> point. Can any one tell me how I can do with for loop. Thanks a lot in
> advance.
>
>
>
>
>
> Thanks & Regards,
>
> SUMANTA BASAK.
>
>
>
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