Look at the R help files for predict.Arima rather than using forecast
to forecast an ARIMA model. You might plot your data and the first
difference and you should be able to come to a conclusion about
stationarity. With your very small data set you need a very
parsimonious model. Knowledge about
Ozcan Asilkan wrote:
> Hello,
>
> I am very new to R and Time Series. I need some help including R codes
> about the following issues. I' ll really appreciate any number of
> answers...
>
> # I have a time series data composed of 24 values:
> myinput = c(n1,n2...,n24);
> # In order to make a f
With 24 values you are asking the impossible from your data. If you
use the standard Box Jenkins approach rather than an automatic ARIMA
and using any prior knowledge of the data you might manage some form
of forecast. Look at graphs of the data and their first differences.
Look at graphs of the
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