Hi list,
I am trying to fit arima model for a grid of 360x161x338 points,
where 360x161 is the spatial dimension and 338 is the number of time steps I
have, which is seasonal. For this purpose I used the auto.arima function in
forecast package. After fitting residuals at each grid in space, the auto
correlations are still significant ( but < 0.2). This make me think that the
data could be spatially correlated as well. In such case is it necesary to
remove spatial autocorelations before fitting models in time and are there
some methods available in R to remove the spatial autocorrelations.
Thanks
nuncio
--
Nuncio.M
Research Scientist
National Center for Antarctic and Ocean research
Head land Sada
Vasco da Gamma
Goa-403804
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