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  1. Journal of Agricultural, Biological, and Environmental Statistics
  2. Journal of Agricultural, Biological, and Environmental Statistics : Volume 11
  3. Journal of Agricultural, Biological, and Environmental Statistics : Volume 11, Issue 1, March 2006
  4. Using the truncated auto-Poisson model for spatially correlated counts of vegetation
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Journal of Agricultural, Biological, and Environmental Statistics : Volume 22
Journal of Agricultural, Biological, and Environmental Statistics : Volume 21
Journal of Agricultural, Biological, and Environmental Statistics : Volume 20
Journal of Agricultural, Biological, and Environmental Statistics : Volume 19
Journal of Agricultural, Biological, and Environmental Statistics : Volume 18
Journal of Agricultural, Biological, and Environmental Statistics : Volume 17
Journal of Agricultural, Biological, and Environmental Statistics : Volume 16
Journal of Agricultural, Biological, and Environmental Statistics : Volume 15
Journal of Agricultural, Biological, and Environmental Statistics : Volume 14
Journal of Agricultural, Biological, and Environmental Statistics : Volume 13
Journal of Agricultural, Biological, and Environmental Statistics : Volume 12
Journal of Agricultural, Biological, and Environmental Statistics : Volume 11
Journal of Agricultural, Biological, and Environmental Statistics : Volume 11, Issue 4, December 2006
Journal of Agricultural, Biological, and Environmental Statistics : Volume 11, Issue 3, September 2006
Journal of Agricultural, Biological, and Environmental Statistics : Volume 11, Issue 2, June 2006
Journal of Agricultural, Biological, and Environmental Statistics : Volume 11, Issue 1, March 2006
Using the truncated auto-Poisson model for spatially correlated counts of vegetation
Spatial sampling design for prediction with estimated parameters
Using SAEM to estimate parameters of models of response to applied fertilizer
Spatio-temporal modeling of fine particulate matter
Estimation of animal location from radio telemetry data with temporal dependencies
A permutation test for quantile regression
Journal of Agricultural, Biological, and Environmental Statistics : Volume 10
Journal of Agricultural, Biological, and Environmental Statistics : Volume 9
Journal of Agricultural, Biological, and Environmental Statistics : Volume 8
Journal of Agricultural, Biological, and Environmental Statistics : Volume 7
Journal of Agricultural, Biological, and Environmental Statistics : Volume 6

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Using the truncated auto-Poisson model for spatially correlated counts of vegetation

Content Provider Springer Nature Link
Author Augustin, Nicole H. McNicol, Jim Marriott, Carol A.
Copyright Year 2006
Abstract With vegetation data there are often physical reasons for believing that the response of neighbors has a direct influence on the response at a particular location. In terms of modeling such scenarios the family of auto-models or Markov random fields is a useful choice. If the observed responses are counts, the auto-Poisson model can be used. There are different ways to formulate the auto-Poisson model, depending on the biological context. A drawback of this model is that for positive autocorrelation the likelihood of the auto-Poisson model is not available in closed form. We investigate how this restriction can be avoided by right truncating the distribution. We review different parameter estimation techniques which apply to auto-models in general and compare them in a simulation study. Results suggest that the method which is most easily implemented via standard statistics software, maximum pseudo-likelihood, gives unbiased point estimates, but its variance estimates are biased. An alternative method, Monte Carlo maximum likelihood, works well but is computer-intensive and not available in standard software. We illustrate the methodology and techniques for model checking with clover leaf counts and seed count data from an agricultural experiment.
Starting Page 1
Ending Page 23
Page Count 23
File Format PDF
ISSN 10857117
Journal Journal of Agricultural, Biological, and Environmental Statistics
Volume Number 11
Issue Number 1
e-ISSN 15372693
Language English
Publisher Springer-Verlag
Publisher Date 2006-01-01
Publisher Place New York
Access Restriction One Nation One Subscription (ONOS)
Subject Keyword Autocorrelation Competition Markov random fields Monte Carlo maximum likelihood Pseudo-likelihood Statistics for Life Sciences, Medicine, Health Sciences Agriculture Environmental Monitoring/Analysis Biostatistics
Content Type Text
Resource Type Article
Subject Applied Mathematics Statistics and Probability Environmental Science Agricultural and Biological Sciences Statistics, Probability and Uncertainty
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