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Modelling spatially sampled proportion processes

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	Paradinas Aranjuelo, Iosu; Pennino, Maria Grazia; López Quílez, Antonio; Marín, Marcial; Bellido Millán, José María; Conesa Guillén, David
	This document is a artículoDate2018
	Este documento está disponible también en : http://hdl.handle.net/10550/64632
	Many ecological processes are measured as proportions and are spatially sampled. In all these cases the standard procedure has long been the transformation of proportional data with the arcsine square root or logit transformation, without considering the spatial correlation in any way. This paper presents a robust regression model to analyse this kind of data using a beta regression and including a spatially correlated term within the Bayesian framework. As a practical example, we apply the proposed approach to a spatio-temporally sampled fishery discard dataset.
	Paradinas Aranjuelo, Iosu Pennino, Maria Grazia López Quílez, Antonio Marín, Marcial Bellido Millán, José María Conesa Guillén, David 2018 Modelling spatially sampled proportion processes Revstat-Statistical Journal 16 1 71 86