In this work we introduce a general framework for distribution-free predictive inference in Geographically Weighted Functional Regression (GWFR) using conformal inference. A prediction band for the functional response variable using a functional estimator of the regression function and a new non conformity mea- sure is thus introduced. We also investigate our procedure for producing prediction bands with locally varying length, in order to adapt the approach in presence of het- eroskedasticity in the data. An application for environmental impact assessment is proposed.
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