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Quantifying expert opinion for modelling fauna habitat distributions

Quantifying expert opinion for modelling fauna habitat distributions The practical elicitation of expert beliefs about logistic regression models is considered. An experiment is reported in which ecologists quantified their prior beliefs about the relationship between various environmental attributes and the habitat distribution of certain rare and endangered fauna. Prior distributions were elicited from the ecologists and combined with sample data to form posterior distributions. The elicitation method was proposed by Garthwaite and Al-Awadhi (2004) and is implemented through an interactive graphical computer program. Classical stepwise logistic regression and alternative forms of prior distribution are compared using cross validation. Data on the environmental attributes have been mapped and stored in a GIS database and the posterior distributions can be used to predict the probability of a species' presence/absence at any site in the database. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Computational Statistics Springer Journals

Quantifying expert opinion for modelling fauna habitat distributions

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References (9)

Publisher
Springer Journals
Copyright
Copyright © 2006 by Springer-Verlag
Subject
Statistics; Statistics, general; Probability and Statistics in Computer Science; Probability Theory and Stochastic Processes; Economic Theory/Quantitative Economics/Mathematical Methods
ISSN
0943-4062
eISSN
1613-9658
DOI
10.1007/s00180-006-0255-x
Publisher site
See Article on Publisher Site

Abstract

The practical elicitation of expert beliefs about logistic regression models is considered. An experiment is reported in which ecologists quantified their prior beliefs about the relationship between various environmental attributes and the habitat distribution of certain rare and endangered fauna. Prior distributions were elicited from the ecologists and combined with sample data to form posterior distributions. The elicitation method was proposed by Garthwaite and Al-Awadhi (2004) and is implemented through an interactive graphical computer program. Classical stepwise logistic regression and alternative forms of prior distribution are compared using cross validation. Data on the environmental attributes have been mapped and stored in a GIS database and the posterior distributions can be used to predict the probability of a species' presence/absence at any site in the database.

Journal

Computational Statistics – Springer Journals

Published: Oct 9, 2006

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