Empirical likelihood based heteroscedasticity diagnostics for varying coefficient partially nonlinear models
Heteroscedasticity diagnostics of error variance is essential before performing some statistical inference work. This paper is concerned with the statistical diagnostics for the varying coefficient partially nonlinear model. We propose a novel diagnostic approach for heteroscedasticity of error vari...
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| Format: | Article |
| Language: | English |
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AIMS Press
2024-12-01
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| Series: | AIMS Mathematics |
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| Online Access: | https://www.aimspress.com/article/doi/10.3934/math.20241652 |
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| author | Cuiping Wang Xiaoshuang Zhou Peixin Zhao |
| author_facet | Cuiping Wang Xiaoshuang Zhou Peixin Zhao |
| author_sort | Cuiping Wang |
| collection | DOAJ |
| description | Heteroscedasticity diagnostics of error variance is essential before performing some statistical inference work. This paper is concerned with the statistical diagnostics for the varying coefficient partially nonlinear model. We propose a novel diagnostic approach for heteroscedasticity of error variance in the model by combining it with the empirical likelihood method. Under some mild conditions, the nonparametric version of the Wilks theorem is obtained. Furthermore, simulation studies and a real data analysis are implemented to evaluate the performances of our proposed approaches. |
| format | Article |
| id | doaj-art-c5a264f2579d4fd9b7c7b44a046e291f |
| institution | Kabale University |
| issn | 2473-6988 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | AIMS Press |
| record_format | Article |
| series | AIMS Mathematics |
| spelling | doaj-art-c5a264f2579d4fd9b7c7b44a046e291f2025-01-23T07:53:25ZengAIMS PressAIMS Mathematics2473-69882024-12-01912347053471910.3934/math.20241652Empirical likelihood based heteroscedasticity diagnostics for varying coefficient partially nonlinear modelsCuiping Wang0Xiaoshuang Zhou1Peixin Zhao2School of Mathematics and Statistics, Shandong University of Technology, Zibo 255022, ChinaCollege of Mathematics and Big Data, Dezhou University, Dezhou 253023, ChinaCollege of Mathematics and Statistics, Chongqing Technology and Business University, Chongqing 400067, ChinaHeteroscedasticity diagnostics of error variance is essential before performing some statistical inference work. This paper is concerned with the statistical diagnostics for the varying coefficient partially nonlinear model. We propose a novel diagnostic approach for heteroscedasticity of error variance in the model by combining it with the empirical likelihood method. Under some mild conditions, the nonparametric version of the Wilks theorem is obtained. Furthermore, simulation studies and a real data analysis are implemented to evaluate the performances of our proposed approaches.https://www.aimspress.com/article/doi/10.3934/math.20241652empirical likelihoodheteroscedasticity diagnosticshypothesis testvarying coefficient partially nonlinear model |
| spellingShingle | Cuiping Wang Xiaoshuang Zhou Peixin Zhao Empirical likelihood based heteroscedasticity diagnostics for varying coefficient partially nonlinear models AIMS Mathematics empirical likelihood heteroscedasticity diagnostics hypothesis test varying coefficient partially nonlinear model |
| title | Empirical likelihood based heteroscedasticity diagnostics for varying coefficient partially nonlinear models |
| title_full | Empirical likelihood based heteroscedasticity diagnostics for varying coefficient partially nonlinear models |
| title_fullStr | Empirical likelihood based heteroscedasticity diagnostics for varying coefficient partially nonlinear models |
| title_full_unstemmed | Empirical likelihood based heteroscedasticity diagnostics for varying coefficient partially nonlinear models |
| title_short | Empirical likelihood based heteroscedasticity diagnostics for varying coefficient partially nonlinear models |
| title_sort | empirical likelihood based heteroscedasticity diagnostics for varying coefficient partially nonlinear models |
| topic | empirical likelihood heteroscedasticity diagnostics hypothesis test varying coefficient partially nonlinear model |
| url | https://www.aimspress.com/article/doi/10.3934/math.20241652 |
| work_keys_str_mv | AT cuipingwang empiricallikelihoodbasedheteroscedasticitydiagnosticsforvaryingcoefficientpartiallynonlinearmodels AT xiaoshuangzhou empiricallikelihoodbasedheteroscedasticitydiagnosticsforvaryingcoefficientpartiallynonlinearmodels AT peixinzhao empiricallikelihoodbasedheteroscedasticitydiagnosticsforvaryingcoefficientpartiallynonlinearmodels |