Dear friends,
I am describing a time series regarding seed crop of a mastseeding
endangeredd tree species in southern Brazil. The time series has data on seed
output for 14 years, what is rather long when we think of field data, but is
unfortunately short regarding time series analysis.
For this reason sophisticated tools as time series modeling is out of
question, but the more basic ones like autocorrelation description should be
done. Texbooks on Time series analysis generally mention autocorrelation plots
as a preliminary device and do not pay much attention to them. I use systat and
discovered that it does not explain how it obtains the 95% envelope around the
autocorrelated values.
Because of that I ask: do you know if I can use in this case
autocorrelation indices normally used for spatial autocorrelation like Moran's
I, for which I can obtain Monte Carlo-generated probabilities using popular
softwares as RookCase? They would function as in transect data, with the
difference that instead of distances along a transect I would have years.
Thanks a lof for any feedback on this!
Alexandre
Dr. Alexandre F. Souza
Programa de Pós-Graduação em Biologia: Diversidade e Manejo da Vida Silvestre
Universidade do Vale do Rio dos Sinos (UNISINOS)
Av. UNISINOS 950 - C.P. 275, São Leopoldo 93022-000, RS - Brasil
Telefone: (051)3590-8477 ramal 1263
Skype: alexfadigas
[EMAIL PROTECTED]
http://www.unisinos.br/laboratorios/lecopop
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