Point and Interval Estimation of Variogram Models Using Spatial Empirical Likelihood

DOI10.1198/016214507000001391zbMath1471.62302OpenAlexW2055633756MaRDI QIDQ3632644

Petruţa C. Caragea, Daniel J. Nordman

Publication date: 12 June 2009

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1198/016214507000001391

zbMATH Keywords

least squares estimatorincreasing domain asymptoticsspatial regressionspatial subsampling

Mathematics Subject Classification ID

Asymptotic properties of nonparametric inference (62G20) Linear regression; mixed models (62J05) Nonparametric estimation (62G05) Nonparametric tolerance and confidence regions (62G15)

Related Items (11)

Empirical likelihood for nonparametric regression models with spatial autoregressive errors ⋮ Finite-sample properties of the adjusted empirical likelihood ⋮ Bayesian semiparametric hierarchical empirical likelihood spatial models ⋮ Empirical likelihood for spatial dynamic panel data models with spatial lags and spatial errors ⋮ Variogram calculations for random fields on regular lattices using quadrature methods ⋮ A general frequency domain method for assessing spatial covariance structures ⋮ On nonparametric variogram estimation ⋮ A review of empirical likelihood methods for time series ⋮ Self‐normalization for Spatial Data ⋮ Empirical likelihood for mixed regressive, spatial autoregressive model based on GMM ⋮ A frequency domain empirical likelihood method for irregularly spaced spatial data

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