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

Loading next page...
 
/lp/springer-journals/quantifying-expert-opinion-for-modelling-fauna-habitat-distributions-rRKJFRMM6c
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 StatisticsSpringer Journals

Published: Oct 9, 2006

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create folders to
organize your research

Export folders, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off