At 18:10 02/06/2011, geojs wrote:
Thanks for the quick reply,
I understand that the predict(zip1A, type = "response") command is computing
the fitted_means and these are different than the probabilities
predict(zip1A, type = "prob"). Although, according to Martin (2005), the
highest probabilities do not simply lead to the true count estimates: "to
get the true estimate of relative mean abundance from the ZIP one must
multiply the estimated relative mean number of individuals at a site by the
probability that the relative mean number of individuals at a site is
generated through a Poisson distribution."
I initially thought that the predicted mean and the observed count could be
compared to estimate the fit of the model, but now I am not sure what to
think with Martin (2005) statement.
When I started using zero-inflated models I found
the vignette enormously helpful not only in
understanding the models but also in teaching a
few R programming ideas which I have used
repeatedly since. I am sure Z is too modest to
say this but it really will repay serious study.
Thank you for your help,
JM
Martin, T.G. et al. (2005) Zero tolerance ecology: improving ecological
inference by modelling the source of zero observations, Ecology Letters,
Volume 8, Issue 11, pages 12351246.
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Michael Dewey
i...@aghmed.fsnet.co.uk
http://www.aghmed.fsnet.co.uk/home.html
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