A central limit theorem for sums of functions of residuals in a high-dimensional regression model with an application to variance homoscedasticity test
We establish a joint central limit theorem for sums of squares and the fourth powers of residuals in a high-dimensional regression model. We then apply this CLT to detect the existence of heteroscedasticity for linear regression models without assuming randomness of covariates when the sample size n...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2020
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/142678 |
| _version_ | 1811691962240073728 |
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| author | Bai, Zhidong Pan, Guangming Yin, Yanqing |
| author2 | School of Physical and Mathematical Sciences |
| author_facet | School of Physical and Mathematical Sciences Bai, Zhidong Pan, Guangming Yin, Yanqing |
| author_sort | Bai, Zhidong |
| collection | NTU |
| description | We establish a joint central limit theorem for sums of squares and the fourth powers of residuals in a high-dimensional regression model. We then apply this CLT to detect the existence of heteroscedasticity for linear regression models without assuming randomness of covariates when the sample size n tends to infinity and the number of covariates p may be fixed or tend to infinity. |
| first_indexed | 2024-10-01T06:28:13Z |
| format | Journal Article |
| id | ntu-10356/142678 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T06:28:13Z |
| publishDate | 2020 |
| record_format | dspace |
| spelling | ntu-10356/1426782020-06-26T07:48:45Z A central limit theorem for sums of functions of residuals in a high-dimensional regression model with an application to variance homoscedasticity test Bai, Zhidong Pan, Guangming Yin, Yanqing School of Physical and Mathematical Sciences Science::Mathematics CLT Dependent Random Variables We establish a joint central limit theorem for sums of squares and the fourth powers of residuals in a high-dimensional regression model. We then apply this CLT to detect the existence of heteroscedasticity for linear regression models without assuming randomness of covariates when the sample size n tends to infinity and the number of covariates p may be fixed or tend to infinity. MOE (Min. of Education, S’pore) 2020-06-26T07:48:45Z 2020-06-26T07:48:45Z 2017 Journal Article Bai, Z., Pan, G., & Yin, Y. (2018). A central limit theorem for sums of functions of residuals in a high-dimensional regression model with an application to variance homoscedasticity test. TEST, 27(4), 896-920. doi:10.1007/s11749-017-0575-x 1133-0686 https://hdl.handle.net/10356/142678 10.1007/s11749-017-0575-x 2-s2.0-85038820493 4 27 896 920 en TEST © 2017 Sociedad de Estadística e Investigación Operativa. All rights reserved. |
| spellingShingle | Science::Mathematics CLT Dependent Random Variables Bai, Zhidong Pan, Guangming Yin, Yanqing A central limit theorem for sums of functions of residuals in a high-dimensional regression model with an application to variance homoscedasticity test |
| title | A central limit theorem for sums of functions of residuals in a high-dimensional regression model with an application to variance homoscedasticity test |
| title_full | A central limit theorem for sums of functions of residuals in a high-dimensional regression model with an application to variance homoscedasticity test |
| title_fullStr | A central limit theorem for sums of functions of residuals in a high-dimensional regression model with an application to variance homoscedasticity test |
| title_full_unstemmed | A central limit theorem for sums of functions of residuals in a high-dimensional regression model with an application to variance homoscedasticity test |
| title_short | A central limit theorem for sums of functions of residuals in a high-dimensional regression model with an application to variance homoscedasticity test |
| title_sort | central limit theorem for sums of functions of residuals in a high dimensional regression model with an application to variance homoscedasticity test |
| topic | Science::Mathematics CLT Dependent Random Variables |
| url | https://hdl.handle.net/10356/142678 |
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