1 |
Smith, R. L., Kolenikov, S. and Cox, L. H. (2003). Spatiotemporal modeling of PM2.5 data with missing values, Journal of Geophysical Research, 108, STS 11-1
|
2 |
Handcock, M. S. and Stein, M. L. (1993). A Bayesian analysis of kriging, Technometrics, 35, 403-410
DOI
ScienceOn
|
3 |
Handcock, M. S. and Wallis, J. R. (1994). An approach to statistical spatio-temporal modeling of meteorological fields, Journal of the American Statistical Association, 89, 368-378
DOI
ScienceOn
|
4 |
Heo, T. Y. and Park, M. S. (2009). Bayesian spatial modeling of precipitation data, Korean Journal of Applied Statistics, 22, 425-433
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DOI
ScienceOn
|
5 |
Karson, M. J., Gaudard, M., Linder, E. and Sinha, D. (1999). Bayesian analysis and computations for spatial prediction (with discussion), Environmental and Ecological Statistics, 6, 147-182
DOI
ScienceOn
|
6 |
Le, N. D. and Zidek, J. V. (1992). Interpolation with uncertain spatial covariance: A Bayesian alter-native to Kriging, Journal of Multivariate Analysis, 43, 351-374
DOI
|
7 |
Park, M. S. and Heo, T. Y. (2009). Seasonal spatial-temporal model for rainfall data of South Korea, Journal of Applied Sciences Research, 5, 565-572
|
8 |
R Development Core Team (2008). R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing. Vienna, Austria, ISBN 3-900051-07-0
|
9 |
Ribeiro, P. J. and Diggle, P. J. (2001). geoR: A package for geostatistical analysis, R-NEWS, 1, 15-18
|
10 |
Roberts, G. O. (1996). Markov Chain Concepts Related to Sampling Algorithms, in Markov Chain Monte Carlo in Practice, edited by W. R. Gilks, S. Richardson and D. J. Spiegeihalter. Chapman & Hall/CRC, London, 45-57
|
11 |
Schabenberger, O. and Gotway, C. A. (2004). Statistical Methods for Spatial Data Analysis, Chapman & Hall/CRC, Florida
|
12 |
Banerjee, S., Carlin, B. P. and Gelfand, A. E. (2004). Hierarchical Modeling and Analysis for Spatial Data, Chapman & Hall/CRC, Florida
|
13 |
Box, G. E. P. and Cox, D. R. (1964). An analysis of transformations, Journal of the Royal Statistical Society, Series B, 26, 211-246
|
14 |
Brown, P. J., Le, N. D. and Zidek, J. V. (1994). Multivariate spatial interpolation and exposure to air pollutants, Canadian Journal of Statistics, 22, 489-509
DOI
ScienceOn
|
15 |
Cressie, N., Frey, J., Harch, B. and Smith, M. (2006). Spatial prediction on a river network, Journal of Agricultural, Biological, and Environmental Statistics, 11, 127-150
DOI
|
16 |
De Oliveira, V., Kedem, B, and Short, D. A. (1997). Bayesian prediction of transformed Gaussian random fields, Journal of the American Statistical Association, 92, 1422-1433
DOI
ScienceOn
|
17 |
Diggle, P. J., Tawn, J. A. and Moyeed, R. A. (1998). Model-based geostatistics (with discussion), Applied Statistics, 47, 299-350
DOI
ScienceOn
|
18 |
Ecker, M. D. and Gelfand, A. E. (1997). Bayesian variogram modeling for an isotropic spatial process, Journal of Agricultural, Biological, and Environmental Statistics, 2, 347-369
DOI
ScienceOn
|
19 |
Finley, A. O., Banerjee, S. and Carlin, B. P. (2008). spBayes: Univariate and Multivariate Spatial Modeling, R package version 0.1-0
|