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Spatial analysis for interval-valued data

Author

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  • Austin Workman
  • Joon Jin Song

Abstract

Symbolic data analysis deals with complex data with symbolic objects, such as lists, histograms, and intervals. Spatial analysis for symbolic data is relatively underexplored. To fill the gap, this paper proposes a statistical framework for spatial interval-valued data (SIVD) analysis. We provide geostatistical methods for spatial prediction, predictive performance measure for prediction assessment, and visualization for mapping SIVD. The proposed methods are illustrated with both simulated and real examples.

Suggested Citation

  • Austin Workman & Joon Jin Song, 2024. "Spatial analysis for interval-valued data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 51(10), pages 1946-1960, July.
    • Handle: RePEc:taf:japsta:v:51:y:2024:i:10:p:1946-1960
    DOI: 10.1080/02664763.2023.2249636
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