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Recursive Estimation of the Spatial Error Model
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DOI：10.1111/gean.12317.png)
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In this paper, we propose a recursive approach to estimate the spatial error model. We compare the suggested methodology with standard estimation procedures and we report a set of Monte Carlo experiments which show that the recursive approach substantially reduces the computational effort affecting the precision of the estimators within reasonable limits. The proposed technique can prove helpful when applied to real-time streams of geographical data that are becoming increasingly available in the big data era. Finally, we illustrate this methodology using a set of earthquake data.
Keyword:
MAXIMUM-LIKELIHOOD-ESTIMATION
AUTOREGRESSIVE MODELS
REGRESSION
期刊
IF:
4.3
论文数:
707
被引数:
4.7K
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引用论文
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Specification and estimation of spatial autoregressive models with autoregressive and heteroskedastic disturbances具有自回归和异方差干扰的空间自回归模型的规范和估计
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