-
1
-
-
47649103974
-
Gaussian predictive process models for large spatial datasets
-
Banerjee S, Gelfand AE, Finley AO, Sang H. 2008. Gaussian predictive process models for large spatial datasets. Journal of the Royal Statistical Society, Series B 70(4): 825-848.
-
(2008)
Journal of the Royal Statistical Society, Series B
, vol.70
, Issue.4
, pp. 825-848
-
-
Banerjee, S.1
Gelfand, A.E.2
Finley, A.O.3
Sang, H.4
-
2
-
-
84855922588
-
-
Spatial wavelet Markov models are more efficient than covariance tapering and process convolution, Lund University, Lund, Sweden. Preprints in Mathematical Sciences 13:2009.
-
Bolin D, Lindgren F. 2009. Spatial wavelet Markov models are more efficient than covariance tapering and process convolution, Lund University, Lund, Sweden. Preprints in Mathematical Sciences 13:2009.
-
(2009)
-
-
Bolin, D.1
Lindgren, F.2
-
3
-
-
79961043012
-
Spatial models generated by nested stochastic partial differential equations, with an application to global ozone mapping
-
Bolin D, Lindgren F. 2011. Spatial models generated by nested stochastic partial differential equations, with an application to global ozone mapping. Annals of Applied Statistics 5(1): 523-550.
-
(2011)
Annals of Applied Statistics
, vol.5
, Issue.1
, pp. 523-550
-
-
Bolin, D.1
Lindgren, F.2
-
9
-
-
0032422974
-
A process-convolution approach to modelling temperatures in the North Atlantic Ocean
-
Higdon D. 1998. A process-convolution approach to modelling temperatures in the North Atlantic Ocean. Environmental and Ecological Statistics 5(2): 173-190.
-
(1998)
Environmental and Ecological Statistics
, vol.5
, Issue.2
, pp. 173-190
-
-
Higdon, D.1
-
11
-
-
79961050814
-
An explicit link between Gaussian fields and Gaussian Markov random fields: the stochastic partial differential equation approach (with discussion)
-
Lindgren F, Rue H, Lindström J. 2011. An explicit link between Gaussian fields and Gaussian Markov random fields: the stochastic partial differential equation approach (with discussion). Journal of the Royal Statistical Society. Series B. Statistical Methodology 73(4): 423-498.
-
(2011)
Journal of the Royal Statistical Society. Series B. Statistical Methodology
, vol.73
, Issue.4
, pp. 423-498
-
-
Lindgren, F.1
Rue, H.2
Lindström, J.3
-
15
-
-
62849120031
-
Approximate Bayesian inference for latent Gaussian models using integrated nested Laplace approximations (with discussion)
-
Rue H, Martino S, Chopin N. 2009. Approximate Bayesian inference for latent Gaussian models using integrated nested Laplace approximations (with discussion). Journal of the Royal Statistical Society, Series B 71(2): 319-392.
-
(2009)
Journal of the Royal Statistical Society, Series B
, vol.71
, Issue.2
, pp. 319-392
-
-
Rue, H.1
Martino, S.2
Chopin, N.3
-
17
-
-
0000659593
-
An introduction to stochastic partial differential equations
-
Walsh J. 1986. An introduction to stochastic partial differential equations. École d'Été de Probabilités de Saint Flour XIV-1984 1180:265-439.
-
(1986)
École d'Été de Probabilités de Saint Flour XIV-1984
, vol.1180
, pp. 265-439
-
-
Walsh, J.1
-
19
-
-
84855942569
-
-
Stationary process approximation for the analysis of large spatial datasets. ISDS Discussion Paper 2005-24, Duke University, Durham, NC.
-
Xia G, Gelfand A. 2005. Stationary process approximation for the analysis of large spatial datasets. ISDS Discussion Paper 2005-24, Duke University, Durham, NC.
-
(2005)
-
-
Xia, G.1
Gelfand, A.2
-
20
-
-
2142734871
-
Inconsistent estimation and asymptotically equal interpolations in model-based geostatistics
-
Zhang H. 2004. Inconsistent estimation and asymptotically equal interpolations in model-based geostatistics. Journal of the American Statistical Association 99(465): 250-261.
-
(2004)
Journal of the American Statistical Association
, vol.99
, Issue.465
, pp. 250-261
-
-
Zhang, H.1
|