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Prediction of spatial functional random processes: comparing functional and spatio-temporal kriging approaches
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.ORCID-id: 0000-0003-1098-0076
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
2019 (Engelska)Ingår i: Stochastic environmental research and risk assessment (Print), ISSN 1436-3240, E-ISSN 1436-3259, Vol. 33, nr 10, s. 1699-1719Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

We present and compare functional and spatio-temporal (Sp.T.) kriging approaches to predict spatial functional random processes (which can also be viewed as Sp.T. random processes). Comparisons with respect to computational time and prediction performance via functional cross-validation is evaluated, mainly through a simulation study but also on a real data set. We restrict comparisons to Sp.T. kriging versus ordinary kriging for functional data (OKFD), since the more flexible functional kriging approaches pointwise functional kriging (PWFK) and the functional kriging total model coincide with OKFD in several situations. Here we formulate conditions under which we show that OKFD and PWFK coincide. From the simulation study, it is concluded that the prediction performance of the two kriging approaches in general is rather equal for stationary Sp.T. processes. However, functional kriging tends to perform better for small sample sizes, while Sp.T. kriging works better for large sizes. For non-stationary Sp.T. processes, with a common deterministic time trend and/or time varying variances and dependence structure, OKFD performs better than Sp.T. kriging irrespective of the sample size. For all simulated cases, the computational time for OKFD was considerably lower compared to those for the Sp.T. kriging methods.

Ort, förlag, år, upplaga, sidor
Springer, 2019. Vol. 33, nr 10, s. 1699-1719
Nyckelord [en]
Functional kriging, Prediction, Spatial functional random processes, Spatio-temporal kriging
Nationell ämneskategori
Sannolikhetsteori och statistik
Identifikatorer
URN: urn:nbn:se:umu:diva-164996DOI: 10.1007/s00477-019-01705-yISI: 000491084300003OAI: oai:DiVA.org:umu-164996DiVA, id: diva2:1368678
Forskningsfinansiär
Vetenskapsrådet, 340-2013-5203Tillgänglig från: 2019-11-08 Skapad: 2019-11-08 Senast uppdaterad: 2019-11-08Bibliografiskt granskad

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Strandberg, JohanSjöstedt de Luna, Sara

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Stochastic environmental research and risk assessment (Print)
Sannolikhetsteori och statistik

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