Eliciting Expert Knowledge for Bayesian Logistic Regression in Species Habitat Modelling
Kynn, Mary (2005) Eliciting Expert Knowledge for Bayesian Logistic Regression in Species Habitat Modelling. PhD thesis, Queensland University of Technology.
This research aims to develop a process for eliciting expert knowledge and incorporating this knowledge as prior distributions for a Bayesian logistic regression model. This work was motivated by the need for less data reliant methods of modelling species habitat distributions. A comprehensive review of the research from both cognitive psychology and the statistical literature provided specific recommendations for the creation of an elicitation scheme. These were incorporated into the design of a Bayesian logistic regression model and accompanying elicitation scheme. This model and scheme were then implemented as interactive, graphical software called ELICITOR created within the BlackBox Component Pascal environment. This software was specifically written to be compatible with existing Bayesian analysis software, winBUGS as an odd-on component. The model, elicitation scheme and software were evaluated through five case studies of various fauna and flora species. For two of these there were sufficient data for a comparison of expert and data-driven models. The case studies confirmed that expert knowledge can be quantified and formally incorporated into a logistic regression model. Finally, they provide a basis for a thorough discussion of the model, scheme and software extensions and lead to recommendations for elicitation research.
Citation countsare sourced monthly fromand citation databases.
These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science generally from 1980 onwards.
Citations counts from theindexing service can be viewed at the linked Google Scholar™ search.
Full-text downloadsdisplays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.
|Item Type:||QUT Thesis (PhD)|
|Supervisor:||Pettitt, Anthony& Low Choy, Samantha|
|Keywords:||Bayesian statistics, component software, elicit, expert knowledge, informative prior, logistic regression, presence absence models, prior, species habitat models|
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Science and Technology|
Past > Schools > Mathematical Sciences
|Department:||Faculty of Science|
|Institution:||Queensland University of Technology|
|Copyright Owner:||Copyright Mary Kynn|
|Deposited On:||03 Dec 2008 13:55|
|Last Modified:||29 Oct 2011 05:42|
Repository Staff Only: item control page