Questions about spatio-temporal modelling

Dear Luca,

Have a look at Blangiarde & Cameletti (2015) Spatial and
Spatio-temporal Bayesian Models with R - INLA ISBN: 978-1-118-32655-8
They describe how you can tackle this problem with mixed models with
correlated random effects.

Best regards,
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature
and Forest
team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
Kliniekstraat 25
1070 Anderlecht
Belgium

To call in the statistician after the experiment is done may be no
more than asking him to perform a post-mortem examination: he may be
able to say what the experiment died of. ~ Sir Ronald Aylmer Fisher
The plural of anecdote is not data. ~ Roger Brinner
The combination of some data and an aching desire for an answer does
not ensure that a reasonable answer can be extracted from a given body
of data. ~ John Tukey


2016-04-17 14:39 GMT+02:00 Luca Candeloro <luca.candeloro at gmail.com>:

Starting from environmental and metereological data, I have defined an
annual count variable (number of favourable events, raster type object).
The purpose of the analysis is to predict the next year favourable events
raster, given the time series (last 15 years).
Working at the pixel level, it would be possible to make a Poisson
regression, but treating pixels independently, would loose spatial
effects...
Which is, in your opinion, the best approach?
Is there a spatio-temporal model for this kind of data that could usefully
combine spatial effect  with time series analysis?
Thanks for any suggestions

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