Publication Results



Code: 34/2015
Title: A separable model for spatial functional data with application to the analysis of the production of waste in Venice province
Date: Friday 26th June 2015
Author(s) : Bernardi, M.s.; Mazza, G.; Ramsay, J.o.; Sangalli, L.m.
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Abstract: We propose a method for the analysis of functional data with complex dependencies, such as spatially dependent curves or time dependent surfaces, over highly textured domains. The models are based on the idea of regression with partial di erential regularizations. We focus in particular on a separable space-time version of the model. Among the various modelling features, the proposed method is able to deal with spatial domains featuring peninsulas, islands and other complex geometries. Space-varying covariate information is included in the model via a semi-parametric framework. The proposed method is compared via simulation studies to other spatio-temporal techniques and it is applied to the analysis of the annual production of waste in the towns of Venice province.

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Stochastic environmental research and risk assessment, 2017, 31(1), 23-38.