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Bayesian Spatial Prediction of Random Space-Time Fields With Application to Mapping PM2.5 Exposure

Author

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  • Kibria B.M.G.
  • Sun L.
  • Zidek J. V.
  • Le N. D.

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Suggested Citation

  • Kibria B.M.G. & Sun L. & Zidek J. V. & Le N. D., 2002. "Bayesian Spatial Prediction of Random Space-Time Fields With Application to Mapping PM2.5 Exposure," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 112-124, March.
    • Handle: RePEc:bes:jnlasa:v:97:y:2002:m:march:p:112-124
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    Cited by:

    1. Soumen Dey & Mohan Delampady & Ravishankar Parameshwaran & N. Samba Kumar & Arjun Srivathsa & K. Ullas Karanth, 2017. "Bayesian Methods for Estimating Animal Abundance at Large Spatial Scales Using Data from Multiple Sources," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 22(2), pages 111-139, June.
    2. Kibria, B.M. Golam, 2006. "The matrix-t distribution and its applications in predictive inference," Journal of Multivariate Analysis, Elsevier, vol. 97(3), pages 785-795, March.
    3. S. De Iaco & M. Palma & D. Posa, 2013. "Prediction of particle pollution through spatio-temporal multivariate geostatistical analysis: spatial special issue," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 97(2), pages 133-150, April.
    4. Liu, Jin Shan & Ip, Wai Cheung & Wong, Heung, 2009. "Predictive inference for singular multivariate elliptically contoured distributions," Journal of Multivariate Analysis, Elsevier, vol. 100(7), pages 1440-1446, August.

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