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.
Impact and interest:
Citation counts are sourced monthly from and citation databases.
Citations counts from theindexing service can be viewed at the linked Google Scholar™ search.
|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 04:11|
|Last Modified:||01 Mar 2012 03:25|
Repository Staff Only: item control page