The Bayesian conditional independence model for measurement error: applications in ecology
Denham, Robert, Falk, Matt, & Mengersen, Kerrie (2011) The Bayesian conditional independence model for measurement error: applications in ecology. Environmental and Ecological Statistics, 18(2), pp. 239-255.
The measurement error model is a well established statistical method for regression problems in medical sciences, although rarely used in ecological studies. While the situations in which it is appropriate may be less common in ecology, there are instances in which there may be benefits in its use for prediction and estimation of parameters of interest. We have chosen to explore this topic using a conditional independence model in a Bayesian framework using a Gibbs sampler, as this gives a great deal of flexibility, allowing us to analyse a number of different models without losing generality. Using simulations and two examples, we show how the conditional independence model can be used in ecology, and when it is appropriate.
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:||Journal Article|
|Keywords:||MCMC, Species' distribution modelling, Otolith measurements|
|Subjects:||Australian and New Zealand Standard Research Classification > MATHEMATICAL SCIENCES (010000)|
Australian and New Zealand Standard Research Classification > ENVIRONMENTAL SCIENCES (050000)
Australian and New Zealand Standard Research Classification > BIOLOGICAL SCIENCES (060000)
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Science and Technology|
Past > Schools > Mathematical Sciences
|Deposited On:||29 Aug 2011 14:11|
|Last Modified:||01 Mar 2012 13:25|
Repository Staff Only: item control page