Statistical modeling of spatial big data: An approach from a functional data analysis perspective

Ramón Giraldo; Sophie Dabo-Niang; Sergio Martinez

doi:10.1016/j.spl.2018.02.025

Journal articles

Statistical modeling of spatial big data: An approach from a functional data analysis perspective

Ramón Giraldo ¹ Sophie Dabo-Niang ^{2, 3} Sergio Martinez ⁴

1 UNAL - Universidad Nacional de Colombia [Bogotà]

2 MODAL - MOdel for Data Analysis and Learning

LPP - Laboratoire Paul Painlevé - UMR 8524, Université de Lille, Sciences et Technologies, Inria Lille - Nord Europe, METRICS - Evaluation des technologies de santé et des pratiques médicales - ULR 2694, Polytech Lille - École polytechnique universitaire de Lille

3 LEM - Lille économie management - UMR 9221

4 IRCCyN - Institut de Recherche en Communications et en Cybernétique de Nantes

Abstract : A literature review on spatial big data analysis is given. We show an application of Universal Kriging to a massive spatial dataset. We also present some perspectives of future work in this field.

Keywords : Functional data Spatial big data Universal kriging

Document type :

Journal articles

Domain :

Mathematics [math] / Statistics [math.ST]

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https://hal.archives-ouvertes.fr/hal-01744181
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Submitted on : Thursday, November 22, 2018 - 4:02:08 PM
Last modification on : Friday, November 27, 2020 - 2:18:03 PM
Long-term archiving on: : Saturday, February 23, 2019 - 2:51:16 PM

Statistical modeling of spatial big data: An approach from a functional data analysis perspective

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Statistical modeling of spatial big data: An approach from a functional data analysis perspective

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