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In many environmental applications involving spatially-referenced data, limitations on the number and locations of observations motivate the need for practical and efficient models for spatial interpolation, or kriging.
[author] Schoenberg, I.I. (1938). Metric spaces and completely monotone functions. Annals of Mathematics 39 811-841
1938
Earlier work this paper cites.
[author] Bochner, SalomonS. (1959). Lectures on Fourier integrals. No. 42. Princeton University Press
1959
Earlier work this paper cites.
[author] Thiébaux, H. JeanH. J. (1976). Anisotropic Correlation Functions for Objective Analysis. Monthly Weather Review 104 994-1002
1976
Earlier work this paper cites.
[author] Mardia, Kanti VK. V., Kent, J TJ. T. and Bibby, J MJ. M. (1979). Multivariate Analysis. Academic Press
1979
Earlier work this paper cites.
[author] Adler, R. J.R. J. (1981). The Geometry of Random Fields. John Wiley & Sons
1981
Earlier work this paper cites.
[author] Thiébaux, H. JeanH. J. and Pedder, M. A.M. A. (1987). Spatial objective analysis: with applications in atmospheric science. Academic Press
1987
Earlier work this paper cites.
[author] Sampson, Paul D.P. D. and Guttorp, PeterP. (1992). Nonparametric Estimation of Nonstationary Spatial Covariance Structure. Journal of the American Statistical Association 87 108-119. 10.1080/01621459.1992.10475181
1992
Earlier work this paper cites.
[author] Barry, Ronald PaulR. P. and Ver Hoef, Jay MJ. M. (1996). Blackbox Kriging: Spatial Prediction without Specifying Variogram Models. Journal of Agricultural, Biological, and Environmental Statistics 1 297-322
1996
Earlier work this paper cites.
[author] Higdon, DavidD. (1998). A process-convolution approach to modelling temperatures in the North Atlantic Ocean. Environmental and Ecological Statistics 5 173-190. 10.1023/A:1009666805688
1998
Earlier work this paper cites.
[author] Hoef, Jay M. VerJ. M. V. and Barry, Ronald PaulR. P. (1998). Constructing and fitting models for cokriging and multivariable spatial prediction. Journal of Statistical Planning and Inference 69 275 - 294. http://dx.doi.org/10.1016/S0378-3758(97)00162-6
1998
Earlier work this paper cites.
[author] Holland, David M.D. M., Saltzman, NancyN., Cox, Lawrence H.L. H. and Nychka, DouglasD. (1998). Spatial prediction of dulfur dioxide in the eastern United States. In GeoENV II: Geostatistics for Environmental Applications. (JaimeJ. Gomez-Hernandez, AmilcarA. Soares and RolandR. Friodevaux, eds.) 65-75. Kluwer Academic Publishers
1998
Earlier work this paper cites.
[author] Ickstadt, KatjaK. and Wolpert, Robert L.R. L. (1998). Spatial regression for marked point processes. Bayesian Statistics 6
1998
Earlier work this paper cites.
[author] Higdon, D.D., Swall, J.J. and Kern, J.J. (1999). Non-Stationary Spatial Modeling. Bayesian Statistics 6
1999
Earlier work this paper cites.
[author] Stein, Michael L.M. L. (1999). Interpolation of spatial data: some theory for kriging. Springer Science & Business Media
1999
Earlier work this paper cites.
[author] Damian, DorisD., Sampson, Paul DP. D. and Guttorp, PeterP. (2001). Bayesian estimation of semi-parametric non-stationary spatial covariance structures. Environmetrics 12 161–178. 10.1002/1099-095X(200103)12:2¡161::AID-ENV452¿3.0.CO;2-G
2001
Cited alongside, same era.
[author] Fuentes, MontserratM. (2001). A high frequency kriging approach for non-stationary environmental processes. Environmetrics 12 469–483. 10.1002/env.473
2001
Cited alongside, same era.
[author] Higdon, DaveD. (2002). Space and Space-Time Modeling using Process Convolutions. In Quantitative Methods for Current Environmental Issues (CliveW.C. Anderson, VicV. Barnett, PhilipC.P. Chatwin and AbdelH.A. El-Shaarawi, eds.) 37-56. Springer London. 10.1007/978-1-4471-0657-9_2
2002
Cited alongside, same era.
[author] Nychka, DouglasD., Wikle, ChristopherC. and Royle, J AndrewJ. A. (2002). Multiresolution models for nonstationary spatial covariance functions. Statistical Modelling 2 315-331. 10.1191/1471082x02st037oa
2002
[author] Wikle, Christopher K.C. K. (2010). Low-rank representations for spatial processes. In Handbook of Spatial Statistics, (A. E.A. E. Gelfand, M.M. Fuentes, P.P. Guttorp and P.P. Diggle, eds.). Chapman & Hall/CRC Handbooks of Modern Statistical Methods Taylor & Francis
2010
Later among the works it cites.
[author] Lindgren, FinnF., Rue, HavardH. and Lindstrom, JohanJ. (2011). An explicit link between Gaussian fields and Gaussian Markov random fields: the stochastic partial differential equation approach. Journal of the Royal Statistical Society: Series B (Statistical Methodology) 73 423–498. 10.1111/j.1467-9868.2011.00777.x
2011
Later among the works it cites.
[author] Reich, Brian J.B. J., Eidsvik, JoJ., Guindani, MicheleM., Nail, Amy J.A. J. and Schmidt, Alexandra M.A. M. (2011). A class of covariate-dependent spatiotemporal covariance functions for the analysis of daily ozone concentration. The Annals of Applied Statistics 5 2425–2447. 10.1214/11-AOAS482
2011
Later among the works it cites.
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Cited alongside, same era.
[author] Paciorek, Christopher JosephC. J. (2003). Nonstationary Gaussian processes for regression and spatial modelling PhD thesis, Carnegie Mellon University
2003
Cited alongside, same era.
[author] Schmidt, Alexandra M.A. M. and O’Hagan, AnthonyA. (2003). Bayesian inference for non-stationary spatial covariance structure via spatial deformations. Journal of the Royal Statistical Society: Series B (Statistical Methodology) 65 743–758. 10.1111/1467-9868.00413
2003
Cited alongside, same era.
[author] Ver Hoef, Jay MJ. M., Cressie, NoelN. and Barry, Ronald PaulR. P. (2004). Flexible Spatial Models for Kriging and Cokriging Using Moving Averages and the Fast Fourier Transform (FFT). Journal of Computational and Graphical Statistics 13 265-282. 10.1198/1061860043498
2004
Cited alongside, same era.
[author] Stein, Michael LM. L. (2005). Nonstationary spatial covariance functions. Unpublished technical report
2005
Cited alongside, same era.
[author] Paciorek, Christopher J.C. J. and Schervish, Mark J.M. J. (2006). Spatial modeling using a new class of nonstationary covariance functions. Environmetrics 17 483-506
2006
Cited alongside, same era.
[author] Calder, Catherine A.C. A. and Cressie, NoelN. (2007). Some Topics in Convolution-Based Spatial Modeling. In Proceedings of the 56th Session of the International Statistics Institute Lisbon, Portugal
2007
Cited alongside, same era.
[author] Anderes, Ethan B.E. B. and Stein, Michael L.M. L. (2008). Estimating deformations of isotropic Gaussian random fields on the plane. The Annals of Statistics 36 719–741. 10.1214/009053607000000893
2008
Cited alongside, same era.
[author] Calder, Catherine A.C. A. (2008). A dynamic process convolution approach to modeling ambient particulate matter concentrations. Environmetrics 19 39–48. 10.1002/env.852
2008
Cited alongside, same era.
[author] Schmidt, Alexandra M.A. M., Guttorp, PeterP. and O’Hagan, AnthonyA. (2011). Considering covariates in the covariance structure of spatial processes. Environmetrics 22 487–500. 10.1002/env.1101
2011
Later among the works it cites.
[author] Kleiber, WilliamW. and Nychka, DouglasD. (2012). Nonstationary modeling for multivariate spatial processes. Journal of Multivariate Analysis 112 76 - 91. http://dx.doi.org/10.1016/j.jmva.2012.05.011
2012
Later among the works it cites.
[author] Ingebrigtsen, RikkeR., Lindgren, FinnF. and Steinsland, IngelinI. (2014). Spatial models with explanatory variables in the dependence structure. Spatial Statistics 8 20 - 38. http://dx.doi.org/10.1016/j.spasta.2013.06.002
2013
Later among the works it cites.
[author] Katzfuss, MatthiasM. (2013). Bayesian nonstationary spatial modeling for very large datasets. Environmetrics 24 189–200. 10.1002/env.2200
2013
Later among the works it cites.
[author] Banerjee, SudiptoS., Carlin, Bradley P.B. P. and Gelfand, Alan E.A. E. (2014). Hierarchical modeling and analysis for spatial data. CRC Press
2014
Later among the works it cites.
[author] Vianna Neto, Joaquim HenriquesJ. H., Schmidt, Alexandra M.A. M. and Guttorp, PeterP. (2014). Accounting for spatially varying directional effects in spatial covariance structures. Journal of the Royal Statistical Society: Series C (Applied Statistics) 63 103–122. 10.1111/rssc.12027
2014
Later among the works it cites.
[author] Risser, Mark D.M. D. (2015). Spatially-Varying Covariance Functions for Nonstationary Spatial Process Modeling. PhD thesis, The Ohio State University. Electronic dissertation, retrieved from https://etd.ohiolink.edu/
2015
Later among the works it cites.
[author] Risser, Mark D.M. D. and Calder, Catherine A.C. A. (2015). Regression-based covariance functions for nonstationary spatial modeling. Environmetrics 26 284–297. 10.1002/env.2336
2015
Later among the works it cites.
[author] Risser, Mark D.M. D. and Calder, Catherine A.C. A. (2016). Local likelihood estimation for covariance functions with spatially-varying parameters: the convoSPAT package for R. ArXiv pre-prints
2016
Closest in time.
[author] Risser, Mark D.M. D., Calder, Catherine A.C. A., Berrocal, Veronica J.V. J. and Berrett, CandaceC. (2016). Nonstationary Spatial Process Modeling Via Treed Covariate Segmentation, with Application to Soil Organic Carbon Stock Assessment. ArXiv pre-prints
2016
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