On Information About Covariance Parameters in Gaussian Matérn Random Fields
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DOI: 10.1007/s13253-022-00510-5
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- Peter Guttorp & Tilmann Gneiting, 2006. "Studies in the history of probability and statistics XLIX On the Matern correlation family," Biometrika, Biometrika Trust, vol. 93(4), pages 989-995, December.
- Stein, Michael L., 1993. "A simple condition for asymptotic optimality of linear predictions of random fields," Statistics & Probability Letters, Elsevier, vol. 17(5), pages 399-404, August.
- Peter Diggle & Søren Lophaven, 2006. "Bayesian Geostatistical Design," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 33(1), pages 53-64, March.
- Zhang, Hao, 2004. "Inconsistent Estimation and Asymptotically Equal Interpolations in Model-Based Geostatistics," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 250-261, January.
- Bachoc, François, 2014. "Asymptotic analysis of the role of spatial sampling for covariance parameter estimation of Gaussian processes," Journal of Multivariate Analysis, Elsevier, vol. 125(C), pages 1-35.
- C. G. Kaufman & B. A. Shaby, 2013. "The role of the range parameter for estimation and prediction in geostatistics," Biometrika, Biometrika Trust, vol. 100(2), pages 473-484.
- Wu, Wei-Ying & Lim, Chae Young & Xiao, Yimin, 2013. "Tail estimation of the spectral density for a stationary Gaussian random field," Journal of Multivariate Analysis, Elsevier, vol. 116(C), pages 74-91.
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Keywords
Fisher information; Geostatistics; Microergodic parameter; Sampling design; Smoothness parameter;All these keywords.
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