Umeå University's logo

umu.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
A comparison of spatiotemporal and functional kriging approaches
Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.ORCID iD: 0000-0003-1098-0076
Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.ORCID iD: 0000-0003-1591-5716
University Jaume I of Castellon, Department of Mathematics, Spain.
2021 (English)In: Geostatistical functional data analysis / [ed] Mateu, Jorge: Giraldo, Ramón, John Wiley & Sons, 2021, p. 375-402Chapter in book (Refereed)
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.

Place, publisher, year, edition, pages
John Wiley & Sons, 2021. p. 375-402
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:umu:diva-208086DOI: 10.1002/9781119387916.ch15Scopus ID: 2-s2.0-85153435149ISBN: 9781119387916 (electronic)ISBN: 9781119387848 (print)OAI: oai:DiVA.org:umu-208086DiVA, id: diva2:1763264
Available from: 2023-06-07 Created: 2023-06-07 Last updated: 2023-06-07Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records

Strandberg, JohanSjöstedt de Luna, Sara

Search in DiVA

By author/editor
Strandberg, JohanSjöstedt de Luna, Sara
By organisation
StatisticsDepartment of Mathematics and Mathematical Statistics
Probability Theory and Statistics

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 94 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf