Discussing the “big n problem”
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[1] David Higdon,et al. Non-Stationary Spatial Modeling , 2022, 2212.08043.
[2] David Ruppert,et al. Tapered Covariance: Bayesian Estimation and Asymptotics , 2012 .
[3] H. Rue,et al. An explicit link between Gaussian fields and Gaussian Markov random fields: the stochastic partial differential equation approach , 2011 .
[4] F. Lindgren,et al. Spatial wavelet Markov models are more efficient than covariance tapering and process convolutions , 2011 .
[5] Andrew O. Finley,et al. Improving the performance of predictive process modeling for large datasets , 2009, Comput. Stat. Data Anal..
[6] H. Rue,et al. Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations , 2009 .
[7] Douglas W. Nychka,et al. Covariance Tapering for Likelihood-Based Estimation in Large Spatial Data Sets , 2008 .
[8] H. Rue,et al. On the Second‐Order Random Walk Model for Irregular Locations , 2008 .
[9] A. Gelfand,et al. Gaussian predictive process models for large spatial data sets , 2008, Journal of the Royal Statistical Society. Series B, Statistical methodology.
[10] N. Cressie,et al. Fixed rank kriging for very large spatial data sets , 2008 .
[11] Yoshihiro Yajima,et al. Fourier analysis of irregularly spaced data on Rd , 2007 .
[12] M. Fuentes. Approximate Likelihood for Large Irregularly Spaced Spatial Data , 2007, Journal of the American Statistical Association.
[13] D. Nychka,et al. Covariance Tapering for Interpolation of Large Spatial Datasets , 2006 .
[14] Jun Yan,et al. Gaussian Markov Random Fields: Theory and Applications , 2006 .
[15] Leonhard Held,et al. Gaussian Markov Random Fields: Theory and Applications , 2005 .
[16] Zhiyi Chi,et al. Approximating likelihoods for large spatial data sets , 2004 .
[17] Sw. Banerjee,et al. Hierarchical Modeling and Analysis for Spatial Data , 2003 .
[18] H. Rue,et al. Fitting Gaussian Markov Random Fields to Gaussian Fields , 2002 .
[19] F. J. Alonso,et al. The Kriged Kalman filter , 1998 .
[20] Holger Wendland,et al. Piecewise polynomial, positive definite and compactly supported radial functions of minimal degree , 1995, Adv. Comput. Math..
[21] T. C. Haas,et al. Local Prediction of a Spatio-Temporal Process with an Application to Wet Sulfate Deposition , 1995 .
[22] P. Guttorp,et al. Nonparametric Estimation of Nonstationary Spatial Covariance Structure , 1992 .
[23] Reuven Y. Rubinstein,et al. Simulation and the Monte Carlo method , 1981, Wiley series in probability and mathematical statistics.
[24] P. Whittle. ON STATIONARY PROCESSES IN THE PLANE , 1954 .
[25] Ying Sun,et al. Geostatistics for Large Datasets , 2012 .
[26] Emilio Porcu,et al. Advances and challenges in space-time modelling of natural events , 2012 .
[27] Montserrat Fuentes,et al. Bayesian modeling for large spatial datasets , 2012, Wiley interdisciplinary reviews. Computational statistics.
[28] Simon P. Wilson,et al. Variant functional approximations for latent Gaussian models ( Technical Report of Statistics department , TCD , 2011 .
[29] H. Rue,et al. An explicit link between Gaussian fields and Gaussian Markov random fields; The SPDE approach , 2010 .
[30] Finn Lindgren,et al. Explicit construction of GMRF approximations to generalised Matérn fields on irregular grids , 2007 .
[31] Hao Zhang,et al. Covariance Tapering in Spatial Statistics , 2007 .
[32] Haotian Hang,et al. Inconsistent Estimation and Asymptotically Equal Interpolations in Model-Based Geostatistics , 2004 .
[33] L. R. Scott,et al. The Mathematical Theory of Finite Element Methods , 1994 .