Open Conference Systems, 50th Scientific meeting of the Italian Statistical Society

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Multivariate analysis of marine litter abundance through Bayesian space-time models
crescenza calculli, Alessio Pollice, Letizia Sion, Porzia Maiorano

Last modified: 2018-05-18


This work focuses on the analysis of abundance data for marine litter categories, collected during trawl surveys regularly conducted at local scale, in the Central Mediterranean. Here marine litter data are modeled in order to estimate the effects affecting the dynamics of litter assemblages at different spatio/temporal scales. A correlated response model with latent variables is proposed. This modeling approach is particularly suitable to infer potential environmental covariates while controlling for correlation between litter categories and providing a method for residual ordination. MCMC estimation is implemented within the Bayesian hierachical framework that allows to integrate environmental and anthropogenic processes into a single model.


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