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A comparison of spatiotemporal and functional kriging approaches
Umeå universitet, Samhällsvetenskapliga fakulteten, Handelshögskolan vid Umeå universitet, Statistik.ORCID-id: 0000-0003-1098-0076
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.ORCID-id: 0000-0003-1591-5716
University Jaume I of Castellon, Department of Mathematics, Spain.
2021 (engelsk)Inngår i: Geostatistical functional data analysis / [ed] Mateu, Jorge: Giraldo, Ramón, John Wiley & Sons, 2021, s. 375-402Kapittel i bok, del av antologi (Fagfellevurdert)
Abstract [en]

Here we present and compare functional and spatiotemporal (Sp.T.) kriging approaches to predict spatial functional random processes, which can also be viewed as Sp.T. random processes. Comparisons are focused on Sp.T. kriging versus ordinary kriging for functional data (OKFD), since more flexible functional kriging approaches like pointwise functional kriging and functional kriging total model coincide with OKFD in several situations. Prediction performance is evaluated via functional cross-validation on simulated data as well as on a Canadian weather data set. The two kriging approaches perform in many cases rather equal for stationary Sp.T. processes. For nonstationary Sp.T. processes, OKFD performs better than Sp.T. kriging. The computational time for OKFD is considerably lower compared to those for the Sp.T. kriging methods.

sted, utgiver, år, opplag, sider
John Wiley & Sons, 2021. s. 375-402
HSV kategori
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URN: urn:nbn:se:umu:diva-208086DOI: 10.1002/9781119387916.ch15Scopus ID: 2-s2.0-85153435149ISBN: 9781119387916 (digital)ISBN: 9781119387848 (tryckt)OAI: oai:DiVA.org:umu-208086DiVA, id: diva2:1763264
Tilgjengelig fra: 2023-06-07 Laget: 2023-06-07 Sist oppdatert: 2023-06-07bibliografisk kontrollert

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Strandberg, JohanSjöstedt de Luna, Sara

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