Towards reconciling two asymptotic frameworks in spatial statistics

By Hao Zhang, Dale L. Zimmerman. 2005

175 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Environmental Engineering, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/ed5640ac7652f1f844dee9be17e0349873ed9f56

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Citations in the corpus

Estimation and prediction using generalized Wendland covariance functions under fixed domain asymptotics (2016, background): “The asymptotic behavior of ML estimators of the covariance parameters can be quite different under these two frameworks (Zhang and Zimmerman, 2005).”
Local linear spatial quantile regression (2009, unknown): “First (detrending), an estimation (μ̂Y (si), μ̂ ′ X(si) ′) of the spatial trend is removed via some adequate spatial smoothing method (that is, smoothing with respect to si); see [1,6,56] for recent discussion.”
Matérn Cross-Covariance Functions for Multivariate Random Fields (2010, methodology): “We now supplement these finite sample results with a view towards the two common forms of spatial asymptotics, infill and increasing domain (Zhang and Zimmerman 2005).”
Tapered Covariance: Bayesian Estimation and Asymptotics (2012, background): “The theoretical results presented here are only possible in the expanding-domain asymptotic regime, which others have argued is less appropriate than the infill regime (Zhang 2004; Zhang and Zimmerman 2005).”
Estimating Space and Space-Time Covariance Functions for Large Data Sets: A Weighted Composite Likelihood Approach (2012, unknown): “For a comparison of these two frameworks, see Zhang and Zimmerman ( 2005 ).”
Optimal Geostatistical Model Selection (2007, methodology): “Some asymptotic properties of the MLEs and REML estimators in Gaussian spatial models have been given by Mardia and Marshall (1984), Cressie and Lahiri (1996), and Zhang and Zimmerman (2005).”
Spatial designs and properties of spatial correlation: Effects on covariance estimation (2007, background): “This is supported by the consistency results for the exponential-without-nugget model (Zhang 2004; Zhang and Zimmerman 2005), which show the product of the parameters is consistent but the individual parameters are not, under in-fill asymptotics.”
Maximum‐likelihood estimation for multivariate spatial linear coregionalization models (2007, background): “Sauer and Meek (2003) studied the spatial variation of plant-available phosphorus in pastures at a site located in Eastern Benton County, Arkansas, USA, where a few variables of soil properties, including phosphorus, N, and C, were measured on soil samples.”