Efficiency of least squares estimators in the presence of spatial autocorrelation

DOI10.1080/03610919308813147zbMath0800.62569OpenAlexW2012802403WikidataQ58810640 ScholiaQ58810640MaRDI QIDQ4275712

Clifford B. Cordy, Daniel A. Griffith

Publication date: 20 January 1994

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610919308813147

Mathematics Subject Classification ID

Inference from spatial processes (62M30) Linear regression; mixed models (62J05) Probabilistic methods, stochastic differential equations (65C99)

Related Items (4)

Testing for Spatial Autocorrelation: The Regressors that Make the Power Disappear ⋮ Efficiency of the OLS estimator in the vicinity of a spatial unit root ⋮ POWER PROPERTIES OF INVARIANT TESTS FOR SPATIAL AUTOCORRELATION IN LINEAR REGRESSION ⋮ On the quality of likelihood-based estimators in spatial autoregressive models when the data dependence structure is misspecified

Cites Work

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• Mean squared prediction error in the spatial linear model with estimated covariance parameters
• Maximum likelihood estimation of models for residual covariance in spatial regression
• Symmetrically distributed and unbiased estimators in linear models
• Spatial Autocorrelation Among Errors and the Relative Efficiency of OLS in the Linear Regression Model
• Finite Sample Efficiency of Ordinary Least Squares in the Linear Regression Model with Autocorrelated Errors
• The inefficiency of least squares
• Estimation Methods for Models of Spatial Interaction
• Efficiency of Least-Squares Estimation of Linear Trend when Residuals Are Autocorrelated

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