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Interpolating Missing Spatial Data Using Graph Laplacian Eigenbasis

Author

Listed:
  • Zihan Jin

    (Graduate School of Humanities and Social Sciences, Hiroshima University, 1-2-1 Kagamiyama, Higashihiroshima 739-8525, Japan)

  • Hiroshi Yamada

    (Faculty of Economics, Kansai University, 3-3-35 Yamate, Suita 564-8680, Japan)

Abstract

This paper addresses the problem of interpolating missing spatial data at the vertices of a connected undirected simple graph. We show that, by exploiting the eigenbasis of the graph Laplacian, all missing values can be reconstructed even from a single observation. This work establishes a novel connection between spatial statistics and spectral graph theory.

Suggested Citation

  • Zihan Jin & Hiroshi Yamada, 2026. "Interpolating Missing Spatial Data Using Graph Laplacian Eigenbasis," Mathematics, MDPI, vol. 14(9), pages 1-11, April.
    • Handle: RePEc:gam:jmathe:v:14:y:2026:i:9:p:1435-:d:1927796
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