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Recursive Estimation of the Spatial Error Model

delete2022-01-03
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PRE
AI
C
Chiara Ghiringhelli *
G
Gianfranco Piras
G
Giuseppe Arbia
A
Antonietta Mira
DOI:10.1111/gean.12317delete
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Abstract

Abstract

En 中文
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.
Keywords:
MAXIMUM-LIKELIHOOD-ESTIMATION
AUTOREGRESSIVE MODELS
REGRESSION

Journal

Geographical Analysis cover
Geographical Analysis
IF:
4.3
Papers:
705
Citations:
4.7K

Organization

U
Universita della Svizzera Italiana
Scholars:
3.3K
Papers: 2.8K
Citations: 3
C
Catholic University of the Sacred Heart
Scholars:
3.1W
Papers: 2.1W
Citations: 22
I
irccs policlinico gemelli
Scholars:
1.8W
Papers: 1.3W
Citations: 9
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