The Bayesian conditional independence model for measurement error: applications in ecology
Data(s) |
2011
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Resumo |
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. |
Formato |
application/pdf |
Identificador | |
Publicador |
Springer New York LLC |
Relação |
http://eprints.qut.edu.au/45509/1/45509.pdf DOI:10.1007/s10651-009-0130-3 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. |
Fonte |
Faculty of Science and Technology; Mathematical Sciences |
Palavras-Chave | #010000 MATHEMATICAL SCIENCES #050000 ENVIRONMENTAL SCIENCES #060000 BIOLOGICAL SCIENCES #MCMC, Species' distribution modelling, Otolith measurements |
Tipo |
Journal Article |