Maximum likelihood estimation of a spatial model typically requires a sizeable computational capacity, even in relatively small samples, and becomes unfeasible in very large datasets. The unilateral approximation approach to spatial models estimation (suggested in Besag, 1974) provides a viable alternative to maximum likelihood estimation that reduces substantially computing time and the storage required. In this paper we extend the method, originally proposed for conditionally specified processes, to simultaneous and to general bilateral spatial processes. We prove the estimators’ consistency and studytheir finite-sample propertiesvia Monte Carlo simulations.

Arbia, G., Bee, M., Espa, G., Santi, F., Fitting spatial regressions to large datasets using unilateral approximations, <<COMMUNICATIONS IN STATISTICS, THEORY AND METHODS>>, 2018; 2018 (47): 222-238. [doi:10.1080/03610926.2017.1301476] [http://hdl.handle.net/10807/116313]

Fitting spatial regressions to large datasets using unilateral approximations

Arbia, Giuseppe;
2018

Abstract

Maximum likelihood estimation of a spatial model typically requires a sizeable computational capacity, even in relatively small samples, and becomes unfeasible in very large datasets. The unilateral approximation approach to spatial models estimation (suggested in Besag, 1974) provides a viable alternative to maximum likelihood estimation that reduces substantially computing time and the storage required. In this paper we extend the method, originally proposed for conditionally specified processes, to simultaneous and to general bilateral spatial processes. We prove the estimators’ consistency and studytheir finite-sample propertiesvia Monte Carlo simulations.
Inglese
Arbia, G., Bee, M., Espa, G., Santi, F., Fitting spatial regressions to large datasets using unilateral approximations, <<COMMUNICATIONS IN STATISTICS, THEORY AND METHODS>>, 2018; 2018 (47): 222-238. [doi:10.1080/03610926.2017.1301476] [http://hdl.handle.net/10807/116313]
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/10807/116313
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