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Infilling Sparse Records of Spatial Fields

Author

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  • Johns C.J.
  • Nychka D.
  • Kittel T.G.F.
  • Daly C.

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Suggested Citation

  • Johns C.J. & Nychka D. & Kittel T.G.F. & Daly C., 2003. "Infilling Sparse Records of Spatial Fields," Journal of the American Statistical Association, American Statistical Association, vol. 98, pages 796-806, January.
    • Handle: RePEc:bes:jnlasa:v:98:y:2003:p:796-806
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    Cited by:

    1. Samira Zahmatkesh & Mohsen Mohammadzadeh, 2021. "Bayesian prediction of spatial data with non-ignorable missingness," Statistical Papers, Springer, vol. 62(5), pages 2247-2268, October.
    2. Toshihiro Hirano & Yoshihiro Yajima, 2013. "Covariance tapering for prediction of large spatial data sets in transformed random fields," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 65(5), pages 913-939, October.
    3. Ganggang Xu & Marc G. Genton, 2017. "Tukey -and- Random Fields," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(519), pages 1236-1249, July.
    4. Waley W. J. Liang & Herbert K. H. Lee, 2019. "Bayesian nonstationary Gaussian process models via treed process convolutions," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 13(3), pages 797-818, September.
    5. Karl Pazdernik & Ranjan Maitra & Douglas Nychka & Stephan Sain, 2018. "Reduced Basis Kriging for Big Spatial Fields," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 80(2), pages 280-300, August.

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