This paper investigates the adequacy of the matrix exponential spatial specifications (MESS) as an alternative to the widely used spatial autoregressive models (SAR). To provide as complete a picture as possible, we extend the analysis to all the main spatial models governed by matrix exponentials comparing them with their spatial autoregressive counterparts. We propose a new implementation of Bayesian parameter estimation for the MESS model with vague prior distributions, which is shown to be precise and computationally efficient. Our implementations also account for spatially lagged regressors. We further allow for location-specific heterogeneity, which we model by including spatial splines. We conclude by comparing the performances of the different model specifications in applications to a real data set and by running simulations. Both the applications and the simulations suggest that the spatial splines are a flexible and efficient way to account for spatial heterogeneities governed by unknown mechanisms.

Strauss, M.e., Mezzetti, M., Leorato, S. (2017). Is a matrix exponential specification suitable for the modeling of spatial correlation structures?. SPATIAL STATISTICS, 20, 221-243 [10.1016/j.spasta.2017.04.003].

Is a matrix exponential specification suitable for the modeling of spatial correlation structures?

Maura Mezzetti;Samantha Leorato
2017-01-01

Abstract

This paper investigates the adequacy of the matrix exponential spatial specifications (MESS) as an alternative to the widely used spatial autoregressive models (SAR). To provide as complete a picture as possible, we extend the analysis to all the main spatial models governed by matrix exponentials comparing them with their spatial autoregressive counterparts. We propose a new implementation of Bayesian parameter estimation for the MESS model with vague prior distributions, which is shown to be precise and computationally efficient. Our implementations also account for spatially lagged regressors. We further allow for location-specific heterogeneity, which we model by including spatial splines. We conclude by comparing the performances of the different model specifications in applications to a real data set and by running simulations. Both the applications and the simulations suggest that the spatial splines are a flexible and efficient way to account for spatial heterogeneities governed by unknown mechanisms.
2017
Pubblicato
Rilevanza internazionale
Articolo
Sì, ma tipo non specificato
Settore SECS-S/01 - STATISTICA
English
Con Impact Factor ISI
Covariance matrix; Matrix exponential; Spatial correlation;
Matrix exponentiaL, Covariance matrix, Spatial correlation
Strauss, M.e., Mezzetti, M., Leorato, S. (2017). Is a matrix exponential specification suitable for the modeling of spatial correlation structures?. SPATIAL STATISTICS, 20, 221-243 [10.1016/j.spasta.2017.04.003].
Strauss, Me; Mezzetti, M; Leorato, S
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/206383
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