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Identifiability Conditions for Spatio-Temporal Bayesian Dynamic Linear Models

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  • Stefano F. Tonellato

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  • Stefano F. Tonellato, 2005. "Identifiability Conditions for Spatio-Temporal Bayesian Dynamic Linear Models," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(1), pages 81-101.
  • Handle: RePEc:mtn:ancoec:0504
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    File URL: ftp://metron.sta.uniroma1.it/RePEc/articoli/2005-4.pdf
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    References listed on IDEAS

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    1. Berger J.O. & De Oliveira V. & Sanso B., 2001. "Objective Bayesian Analysis of Spatially Correlated Data," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1361-1374, December.
    2. Le, Nhu D. & Zidek, James V., 1992. "Interpolation with uncertain spatial covariances: A Bayesian alternative to Kriging," Journal of Multivariate Analysis, Elsevier, vol. 43(2), pages 351-374, November.
    3. Gabriel Huerta & Bruno Sansó & Jonathan R. Stroud, 2004. "A spatiotemporal model for Mexico City ozone levels," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 53(2), pages 231-248.
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    Cited by:

    1. Chiara Mazzetta & Steve Brooks & Stephen N. Freeman, 2007. "On Smoothing Trends in Population Index Modeling," Biometrics, The International Biometric Society, vol. 63(4), pages 1007-1014, December.

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