Information criteria for matrix exponential spatial specifications

Osman Doğan, Ye Yang*, Süleyman Taşpınar

*Bu çalışma için yazışmadan sorumlu yazar

Araştırma sonucu: ???type-name???Makalebilirkişi

1 Atıf (Scopus)

Özet

In this study, we suggest using information criteria for nested and non-nested model selection problems for the matrix exponential spatial specifications (MESS) under both homoskedasticity and heteroskedasticity. To this end, we consider the deviance information criterion, the Akaike information criterion and the Bayesian information criterion in a Bayesian setting. In the heteroskedastic case, we assume that the error terms have a scale mixture of normal distributions, where the scale mixture variables are latent variables that lead to different distributions. We demonstrate how the integrated likelihood function can be obtained analytically by integrating out the scale mixture variables from the complete-data likelihood function, and how this integrated likelihood function can be used to formulate the information criteria. We investigate the finite sample performance of these criteria in selecting the true model in a simulation study. The results show that these criteria perform satisfactorily and can be useful for selecting the correct model in specification search exercises. Finally, we apply the proposed information criteria to a spatially augmented growth model and a carbon emission model to show their usefulness for both nested and non-nested model selection problems.

Orijinal dilİngilizce
Makale numarası100776
DergiSpatial Statistics
Hacim57
DOI'lar
Yayın durumuYayınlandı - Eki 2023

Bibliyografik not

Publisher Copyright:
© 2023 Elsevier B.V.

Finansman

We thank the editor, the associate editor, and an anonymous referee for many useful comments on the earlier versions. Ye Yang gratefully acknowledges the financial support from the research fund for new professors at Capital University of Economics and Business ( XRZ2023042 ) and the Special Research Fund of Beijing for Capital University of Economics and Business ( ZD202104 ).

FinansörlerFinansör numarası
Special Research Fund of Beijing for Capital University of Economics and BusinessZD202104
Capital University of Economics and BusinessXRZ2023042

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