Least Squares Variogram Fitting by Spatial Subsampling

DOI10.1111/1467-9868.00364zbMath1067.62100OpenAlexW2152822776MaRDI QIDQ4672165

Yoon-Dong Lee, Soumendra Nath Lahiri

Publication date: 29 April 2005

Published in: Journal of the Royal Statistical Society Series B: Statistical Methodology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/1467-9868.00364

zbMATH Keywords

Increasing domain asymptoticsSpatial regressionGeneralized least squares estimator

Mathematics Subject Classification ID

Inference from spatial processes (62M30) Random fields; image analysis (62M40) Asymptotic distribution theory in statistics (62E20) Nonparametric estimation (62G05)

Related Items (10)

Composite likelihood inference for multivariate Gaussian random fields ⋮ Resampling methods for spatial regression models under a class of stochastic designs ⋮ An empirical likelihood method for spatial regression ⋮ Estimating Space and Space-Time Covariance Functions for Large Data Sets: A Weighted Composite Likelihood Approach ⋮ Self‐normalization for Spatial Data ⋮ Comparing composite likelihood methods based on pairs for spatial Gaussian random fields ⋮ Subsampling Variance Estimation for Non‐stationary Spatial Lattice Data ⋮ Recent developments in bootstrap methodology ⋮ Frequency domain bootstrap methods for random fields ⋮ Improved generalized method of moments estimators for weakly dependent observations

Cites Work

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• Mixing: Properties and examples
• Nonparametric resampling for homogeneous strong mixing random fields

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