Ronaldo Reis-Jr.
2006-Jun-06 16:31 UTC
[R] [OFF] The "best" tool for a space-temporal analyses?
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 -- I haven't been married in over six years, but we had sexual counseling every day from Oral Roberts!! -- |> // | \\ [***********************************] | ( ? ? ) [Prof. Ronaldo Reis J?nior ] |> V [UNIMONTES/Depto. Biologia Geral ] | / \ [36570-000 Vi?osa - MG ] |> /(.''`.)\ [Fone: 31-3899-4007 ] | /(: :' :)\ [chrysopa em insecta.ufv.br ] |>/ (`. `'` ) \[ICQ#: 5692561 | LinuxUser#: 205366 ] | ( `- ) [***********************************] |>> _/ \_Powered by GNU/Debian Testing -- Se pelo menos pudessemos viver duas vezes: a primeira vez, para cometer todos os inevitaveis erros; a segunda para lucrar com eles. -- D. H. Lawrence -- |> // | \\ [***********************************] | ( ? ? ) [Prof. Ronaldo Reis J?nior ] |> V [UNIMONTES/Depto. Biologia Geral ] | / \ [36570-000 Vi?osa - MG ] |> /(.''`.)\ [Fone: 31-3899-4007 ] | /(: :' :)\ [chrysopa em insecta.ufv.br ] |>/ (`. `'` ) \[ICQ#: 5692561 | LinuxUser#: 205366 ] | ( `- ) [***********************************] |>> _/ \_Powered by GNU/Debian Testing
Spencer Graves
2006-Jun-08 04:01 UTC
[R] [OFF] The "best" tool for a space-temporal analyses?
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
>