[R] [OFF] The "best" tool for a space-temporal analyses?

Spencer Graves spencer.graves at pdf.com
Thu Jun 8 06:01:08 CEST 2006


	  Have you tried RSiteSearch("spatial ecology")?  I just got 47 hits 
from that.  Some of them might be relevant to your question.

	  If that fails, you might consider providing this group with the math 
behind the automata models you are considering.  I might expect them to 
be expressed in terms of Markov chain (or Markov random field) 
probability models with parameters to be estimated.  The standard 
statistical approach is to consider a sequence of different models, with 
at least some of them nested, with increasing numbers of parameters and 
levels of complexity.  We then estimate the parameters to maximize the 
likelihood (= probability of what was observed given the data).  Testing 
typically assumes that 2*log(likelihood ratio) is approximately 
chi-square, with additional precision given by simulation if desired.

	  Hope this helps.
	  Spencer Graves

Ronaldo Reis-Jr. wrote:
> Hi,
> 
> I try to make an analyses to discover what is the time that an area begin to 
> have spacial autocorrelation. And after, what is the number of individuals 
> responsible for this autocorrelation.
> 
> The main idea is to discover if exist a contamination of a quadrat from others 
> quadrats and how is the population needed to make this contamination.
> 
> This is very common to use automata to simulate this situation. But I try to 
> make a more statistical approach. I'm studing about, but I dont know the tool 
> for testing examples.
> 
> I make an example just for tests:
> 
> Geodata <- data.frame(X=rep(rep(c(1:10),
> (rep(10,10))),5),Y=rep(c(1:10),50),Abund=c(1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 
> 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 
> 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 2, 0, 0, 2, 0, 0, 3, 0, 0, 2, 0, 0, 1, 2, 0, 0, 
> 2, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 3, 0, 0, 0, 2, 0, 0, 0, 
> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 2, 0, 0, 
> 0, 0, 2, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 4, 0, 0, 0, 0, 5, 
> 0, 2, 0, 0, 0, 0, 3, 0, 0, 2, 0, 0, 0, 0, 1, 0, 0, 0, 2, 3, 0, 0, 3, 0, 0, 3, 
> 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 2, 0, 0, 4, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 
> 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 2, 10, 0, 0, 3, 0, 0, 0, 0, 3, 
> 3, 4, 2, 0, 0, 0, 1, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 3, 0, 3, 0, 
> 0, 0, 0, 4, 0, 2, 1, 0, 0, 3, 0, 0, 0, 2, 0, 1, 4, 0, 0, 4, 0, 0, 4, 0, 0, 0, 
> 0, 0, 4, 0, 0, 0, 0, 0, 3, 0, 0, 5, 0, 0, 0, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
> 0, 0, 0, 0, 4, 0, 0, 0, 0, 0, 0, 4, 10, 15, 0, 0, 4, 0, 0, 0, 0, 8, 11, 9, 0, 
> 0, 0, 0, 0, 0, 0, 1, 5, 3, 0, 0, 0, 0, 0, 4, 0, 0, 0, 0, 4, 0, 4, 0, 0, 0, 0, 
> 5, 0, 0, 2, 0, 0, 0, 0, 2, 0, 0, 1, 0, 5, 0, 0, 5, 0, 0, 5, 0, 0, 0, 0, 0, 0, 
> 0, 0, 0, 0, 0, 4, 0, 0, 6, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
> 0, 0, 0, 0, 0, 0, 0, 3, 10, 15, 20, 0, 0, 0, 0, 0, 0, 4, 13, 16, 13, 0, 0, 0, 
> 0, 0, 0, 5, 8, 8, 10, 0, 0, 0, 0, 0, 0, 1, 2, 3, 5, 0, 0, 0, 0, 0, 0, 0, 0, 
> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
> 0),Time=rep(c(1:5),rep(100,5)))
> 
> X and Y are coordinates, Abund is the number of individuals and Time is the 
> date of observation. In this example the population grows from an vertice, 
> and after 10 individuals it contaminates your neighbors. I need ideas about 
> the best approach and R's tools for this problem.
> 
> I'm studing this question in these books:
> 
> W.N. Venables, B.D. Ripley. 2003.  Modern Applied Statistics with S. Springer; 
> 4 edition (September 2, 2003). 512 pages.
> 
> Crawley, M. J. 2002. Statistical Computing: An Introduction to Data Analysis 
> using S-Plus. John Wiley & Sons; 1st edition (May 15, 2002). 772 pages.
> 
> Diggle, Peter J. 2003. Statistical Analysis of Spatial Point Patterns (2nd 
> ed.), Arnold, London.
> 
> Ripley, B.D. Spatial Statistics
> 
> Spatial Ecology
> 
> Thanks for all
>



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