We predict a curve at an unmonitored site taking into account exogenous variables using a functional kriging model with external drift and, alternatively, an additive model with a spatio-temporal smooth term. To evaluate uncertainty of the predicted curves, a semi-parametric bootstrap approach is used for the first, while standard inference is used for the second. The performance of both approaches is illustrated on pollutant functional data.

Kriging for functional data: uncertainty assessment

IGNACCOLO, Rosaria;FRANCO VILLORIA, Maria
2014-01-01

Abstract

We predict a curve at an unmonitored site taking into account exogenous variables using a functional kriging model with external drift and, alternatively, an additive model with a spatio-temporal smooth term. To evaluate uncertainty of the predicted curves, a semi-parametric bootstrap approach is used for the first, while standard inference is used for the second. The performance of both approaches is illustrated on pollutant functional data.
47th SIS Scientific Meeting of the Italian Statistica Society
Cagliari
June 2014
47th Scientific Meeting of the Italian Statistical Society P R O C E E D I N G S
CUEC Cooperativa Universitaria Editrice Cagliaritana
1
6
9788884678744
http://www.sis2014.it/proceedings/allpapers/2953.pdf
Rosaria Ignaccolo; Maria Franco Villoria
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/145817
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