[R-sig-Geo] analyse geo-time data

[Tomislav Hengl]

Dear Katona,

R (i.e. its packages) are definitively suited for analysis of spatio-temporal data. Try searching
the packages in the [http://cran.r-project.org/web/views/Environmetrics.html] views; in fact, there
is a section dedicated to time-series [http://cran.r-project.org/web/views/TimeSeries.html].

There are several good papers on spatio-temporal interpolation e.g.:

Pebesma, E.J., Duin, R.N.M., Burrough, P.A., 2005. Mapping sea bird densities over the North Sea:
spatially aggregated estimates and temporal changes. Environmetrics 16(6), 573--587.
http://dx.doi.org/10.1002/env.723 
(The authors claim to have put the R script on-line but I could not locate them anymore) 

If you are interested in the analysis of time-series data, take a look at this book:

Chatfield, C., 2003. The Analysis of Time Series: An Introduction (6th edition). CRC Press, pp. 352.
http://people.bath.ac.uk/mascc/TS 

Dynamic modeling of spatial phenomena is more difficult (e.g. dynamic simulation of flu spreading).
Maybe you should consider using some diffusion algorithm from ecology? E.g.: diffusion function
implemented in the "simecol" package:

http://bm2.genes.nig.ac.jp/RGM2/pkg.php?p=simecol 

Or maybe consider using some hydrological flow models as implemented in e.g. SAGA GIS.


Few remaining questions:
1. What kind of variables are your talking about? Give some examples.
2. Does your data has a point support or is it areal (polygons)?


HTH,

Tom Hengl
http://spatial-analyst.net 




> -----Original Message-----
> From: r-sig-geo-bounces at stat.math.ethz.ch [mailto:r-sig-geo-bounces at stat.math.ethz.ch] On Behalf
> Of Katona Lajos
> Sent: Thursday, January 08, 2009 10:30 PM
> To: r-sig-geo at stat.math.ethz.ch
> Subject: [R-sig-Geo] analyse geo-time data
> 
> Dear all,
> 
> can you suggest/advise statistical methode in R to analyse my time series and regional/spatial
> data?
> I have 174 region and daily (365) data for every region (geo-time data). (There is 174*365=63510
> data/observation)
> 
> How can I building a model what is founded on parameters of spatial and time series.
> 
> I'd like to simulate how to expand a contagious disease (flu). Find typical patterns and paths.
> 
> What do you think what is the best way to discover and analyse my data?
> 
> Thank you in anticipation,
> Lajos Katona
> 
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