Variable selection in generalized random coefficient autoregressive models

In this paper, we consider the variable selection problem of the generalized random coefficient autoregressive model (GRCA). Instead of parametric likelihood, we use non-parametric empirical likelihood in the information theoretic approach. We propose an empirical likelihood-based Akaike information...

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Detalles Bibliográficos
Autores principales: Zhao, Zhiwen, Liu, Yangping, Peng, Cuixin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2018
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5897497/
https://www.ncbi.nlm.nih.gov/pubmed/29674836
http://dx.doi.org/10.1186/s13660-018-1680-4
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author Zhao, Zhiwen
Liu, Yangping
Peng, Cuixin
author_facet Zhao, Zhiwen
Liu, Yangping
Peng, Cuixin
author_sort Zhao, Zhiwen
collection PubMed
description In this paper, we consider the variable selection problem of the generalized random coefficient autoregressive model (GRCA). Instead of parametric likelihood, we use non-parametric empirical likelihood in the information theoretic approach. We propose an empirical likelihood-based Akaike information criterion (AIC) and a Bayesian information criterion (BIC).
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spelling pubmed-58974972018-04-17 Variable selection in generalized random coefficient autoregressive models Zhao, Zhiwen Liu, Yangping Peng, Cuixin J Inequal Appl Research In this paper, we consider the variable selection problem of the generalized random coefficient autoregressive model (GRCA). Instead of parametric likelihood, we use non-parametric empirical likelihood in the information theoretic approach. We propose an empirical likelihood-based Akaike information criterion (AIC) and a Bayesian information criterion (BIC). Springer International Publishing 2018-04-12 2018 /pmc/articles/PMC5897497/ /pubmed/29674836 http://dx.doi.org/10.1186/s13660-018-1680-4 Text en © The Author(s) 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Research
Zhao, Zhiwen
Liu, Yangping
Peng, Cuixin
Variable selection in generalized random coefficient autoregressive models
title Variable selection in generalized random coefficient autoregressive models
title_full Variable selection in generalized random coefficient autoregressive models
title_fullStr Variable selection in generalized random coefficient autoregressive models
title_full_unstemmed Variable selection in generalized random coefficient autoregressive models
title_short Variable selection in generalized random coefficient autoregressive models
title_sort variable selection in generalized random coefficient autoregressive models
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5897497/
https://www.ncbi.nlm.nih.gov/pubmed/29674836
http://dx.doi.org/10.1186/s13660-018-1680-4
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AT liuyangping variableselectioningeneralizedrandomcoefficientautoregressivemodels
AT pengcuixin variableselectioningeneralizedrandomcoefficientautoregressivemodels

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