[R-sig-eco] Handling lots of zero + spatial autocorrelation

[Peter Solymos]

Claudia,

Here is a more specific paper with hierarchical Bayesian model:
	
Stephen L. Rathbun and Songlin Fei
A spatial zero-inflated poisson regression model for oak regeneration
Environmental and Ecological Statistics, 2006, 13: 409-426
http://www.springerlink.com/content/r327264t016x2873/

I am not sure if the zero probability part is fully identifiable, but
if you use a constant probability model for the zeros, that might work
out even better. (The paper comes with no R implementation.)

Peter

Péter Sólymos
Alberta Biodiversity Monitoring Institute
and Boreal Avian Modelling project
Department of Biological Sciences
CW 405, Biological Sciences Bldg
University of Alberta
Edmonton, Alberta, T6G 2E9, Canada
Phone: 780.492.8534
Fax: 780.492.7635



2010/3/25 Etienne Laliberté <etiennelaliberte at gmail.com>:
> Hi Claudia,
>
> I think you'll find the following article most useful:
>
> Dormann, C. F., J. M. McPherson, M. B. Araujo, R. Bivand, J. Bolliger,
> G. Carl, R. G. Davies, A. Hirzel, W. Jetz, W. Daniel Kissling, I. Kuhn,
> R. Ohlemuller, P. R. Peres-Neto, B. Reineking, B. Schroder, F. M.
> Schurr, et R. Wilson. 2007. Methods to account for spatial
> autocorrelation in the analysis of species distributional data: a
> review. Ecography 30:609-628.
>
> Cheers
>
> Etienne
>
> Le jeudi 25 mars 2010 à 12:00 +0100, r-sig-ecology-request at r-project.org
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>>    1. Handling lots of zero + spatial autocorrelation
>>       (Claudia liliana Ballesteros Mejia)
>>
>>
>> ----------------------------------------------------------------------
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>> Message: 1
>> Date: Wed, 24 Mar 2010 12:28:01 -0700 (PDT)
>> From: Claudia liliana Ballesteros Mejia <lailaliana78 at yahoo.com>
>> To: R-list <r-sig-ecology at r-project.org>
>> Subject: [R-sig-eco] Handling lots of zero + spatial autocorrelation
>> Message-ID: <344339.76193.qm at web112706.mail.gq1.yahoo.com>
>> Content-Type: text/plain
>>
>> Dear list,
>>
>> I'm trying to model the distribution of records that I have collected in my study area affected by parameters as population density and access. I have non normal distribution of the data,  lots of zeros and an important level of spatial autocorrelation. So, I wonder if there is a way in R to handle at the same time the 3 problems, because so far, I've tried the zero inflation poisson regression but it doesn't take into account the spatial autocorrelation, and gls, but it doesn't solve my problem of the zeros and nonnormal distribution.
>>
>> I would appreciate any hint,
>>
>> Liliana.
>>
>>
>>
>>
>>       [[alternative HTML version deleted]]
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>>
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>
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> Etienne Laliberté
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