Modelling spatially sampled proportion processes​​

Modelling spatially sampled proportion processes​​

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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

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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
distribuido bajo licencia Creative Commons de Reconocimiento-NoComercial 3.0 No adaptada

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