Identifiability Conditions for Spatio-Temporal Bayesian Dynamic Linear Models
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Bibliographic InfoArticle provided by Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome in its journal Metron.
Volume (Year): LXIII (2005)
Issue (Month): 1 ()
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- 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.
- Harvey,Andrew C., 1991.
"Forecasting, Structural Time Series Models and the Kalman Filter,"
Cambridge University Press, number 9780521405737, November.
- Harvey,Andrew C., 1990. "Forecasting, Structural Time Series Models and the Kalman Filter," Cambridge Books, Cambridge University Press, number 9780521321969, November.
- 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.
- 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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