Variable selection in generalized random coefficient autoregressive models
Abstract 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 in...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2018-04-01
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| Series: | Journal of Inequalities and Applications |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s13660-018-1680-4 |
| _version_ | 1819169299551485952 |
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| author | Zhiwen Zhao Yangping Liu Cuixin Peng |
| author_facet | Zhiwen Zhao Yangping Liu Cuixin Peng |
| author_sort | Zhiwen Zhao |
| collection | DOAJ |
| description | Abstract 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). |
| first_indexed | 2024-12-22T19:17:18Z |
| format | Article |
| id | doaj.art-252467bbfb184e3da89af6247d19c18c |
| institution | Directory Open Access Journal |
| issn | 1029-242X |
| language | English |
| last_indexed | 2024-12-22T19:17:18Z |
| publishDate | 2018-04-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Journal of Inequalities and Applications |
| spelling | doaj.art-252467bbfb184e3da89af6247d19c18c2022-12-21T18:15:29ZengSpringerOpenJournal of Inequalities and Applications1029-242X2018-04-012018111410.1186/s13660-018-1680-4Variable selection in generalized random coefficient autoregressive modelsZhiwen Zhao0Yangping Liu1Cuixin Peng2College of Mathematics, Jilin Normal UniversityCollege of Mathematics, Jilin Normal UniversityPublic Foreign Languages Department, Jilin Normal UniversityAbstract 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).http://link.springer.com/article/10.1186/s13660-018-1680-4Empirical likelihoodAkaike information criterionBayesian information criterionGeneralized random coefficient autoregressive modelVariable selection |
| spellingShingle | Zhiwen Zhao Yangping Liu Cuixin Peng Variable selection in generalized random coefficient autoregressive models Journal of Inequalities and Applications Empirical likelihood Akaike information criterion Bayesian information criterion Generalized random coefficient autoregressive model Variable selection |
| 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 | Empirical likelihood Akaike information criterion Bayesian information criterion Generalized random coefficient autoregressive model Variable selection |
| url | http://link.springer.com/article/10.1186/s13660-018-1680-4 |
| work_keys_str_mv | AT zhiwenzhao variableselectioningeneralizedrandomcoefficientautoregressivemodels AT yangpingliu variableselectioningeneralizedrandomcoefficientautoregressivemodels AT cuixinpeng variableselectioningeneralizedrandomcoefficientautoregressivemodels |