On asymptotic distribution and asymptotic efficiency of least squares estimators of spatial variogram parameters

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A Nonparametric Test for Spatial Isotropy Using Subsampling (2004, methodology): “Alternative approaches were proposed by Lahiri, Lee, and Cressie (2002), who considered both a “pure-increasing-domain” case and a “mixedincreasing-domain” case.”
Moving window kriging with geographically weighted variograms (2010, background): “Such variographic specifications are chosen so as to minimise the occurrence of a poor (or failed) WLS fit and are crucial in determining a good kriging model performance (see Müller 1999; Lahiri et al. 2002).”
Estimating Space and Space-Time Covariance Functions for Large Data Sets: A Weighted Composite Likelihood Approach (2012, unknown): “By (N1) and Lemma A.1 and Theorem 3.3 in Lahiri, Lee, and Cressie (2002), we have Jn(θ0) = var ( |R̊n|1/2Q̃(1)n (θ0) ) → J (θ0) = 1 4 (θ0)B(θ0) (θ0)B(θ0) ′ (θ0)′, where the (i, j )th element of (θ0) is given by ij (θ0) = ∑ s∈Zd+1 covθ0 [(Z(0) − Z(hi))2, (Z(s) − Z(s + hi))2)], 1 ≤ i, j ≤ p…”