[R-sig-Geo] Questions about spatio-temporal modelling

Thierry Onkelinx thierry.onkelinx at inbo.be
Mon Apr 18 08:49:01 CEST 2016

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

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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