A penalized quasi-maximum likelihood method for variable selection in the spatial autoregressive model

Xuan Liu; Jianbao Chen; Suli Cheng

doi:10.1016/j.spasta.2018.05.001

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A penalized quasi-maximum likelihood method for variable selection in the spatial autoregressive model

Xuan Liu Jianbao Chen Suli Cheng

Year: 2018 Journal: Spatial Statistics Vol: 25 Pages: 86-104 Publisher: Elsevier BV

DOI: 10.1016/j.spasta.2018.05.001

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Keywords:

Autoregressive model Estimator Selection (genetic algorithm) Oracle Consistency (knowledge bases) Model selection Feature selection Maximum likelihood Variable (mathematics) Computer science Mathematics Statistics Mathematical optimization Artificial intelligence

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Spatial and Panel Data Analysis

Social Sciences → Economics, Econometrics and Finance → Economics and Econometrics

Housing Market and Economics

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Regional Economics and Spatial Analysis

Social Sciences → Economics, Econometrics and Finance → Economics and Econometrics

A penalized quasi-maximum likelihood method for variable selection in the spatial autoregressive model

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