In community ecology studies the goal is to evaluate the effect of environmental covariates on a response variable while investigating the nature unobserved heterogeneity. We focus on onefactor mixed models in a Bayesian setting and introduce an intuitive Penalized Complexity (PC) prior to balance the variance components of the model. We start with the simple one-way anova and discuss extension to spatially structured residuals, following a Matern exponential covariance.

(2019). Prior specification in one-factor mixed models applied to community ecology data [poster communication - poster]. Retrieved from http://hdl.handle.net/10446/146898

Prior specification in one-factor mixed models applied to community ecology data

2019

Abstract

In community ecology studies the goal is to evaluate the effect of environmental covariates on a response variable while investigating the nature unobserved heterogeneity. We focus on onefactor mixed models in a Bayesian setting and introduce an intuitive Penalized Complexity (PC) prior to balance the variance components of the model. We start with the simple one-way anova and discuss extension to spatially structured residuals, following a Matern exponential covariance.
Ventrucci, M.; Burgazzi, G.; Cocchi, D.; Laini, A.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/10446/146898
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