Statistical inference on kurtosis of elliptical distributions
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
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| _version_ | 1866910573576323072 |
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| author | Zhou, Bowen Xu, Peirong Wang, Cheng |
| author_facet | Zhou, Bowen Xu, Peirong Wang, Cheng |
| contents | Multivariate elliptically-contoured distributions are widely used for modeling correlated and non-Gaussian data. In this work, we study the kurtosis of the elliptical model, which is an important parameter in many statistical analysis. Based on U-statistics, we develop an estimation method. Theoretically, we show that the proposed estimator is consistent under regular conditions, especially we relax a moment condition and the restriction that the data dimension and the sample size are of the same order. Furthermore, we derive the asymptotic normality of the estimator and evaluate the asymptotic variance through several examples, which allows us to construct a confidence interval. The performance of our method is validated by extensive simulations and real data analysis. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_12131 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Statistical inference on kurtosis of elliptical distributions Zhou, Bowen Xu, Peirong Wang, Cheng Statistics Theory Multivariate elliptically-contoured distributions are widely used for modeling correlated and non-Gaussian data. In this work, we study the kurtosis of the elliptical model, which is an important parameter in many statistical analysis. Based on U-statistics, we develop an estimation method. Theoretically, we show that the proposed estimator is consistent under regular conditions, especially we relax a moment condition and the restriction that the data dimension and the sample size are of the same order. Furthermore, we derive the asymptotic normality of the estimator and evaluate the asymptotic variance through several examples, which allows us to construct a confidence interval. The performance of our method is validated by extensive simulations and real data analysis. |
| title | Statistical inference on kurtosis of elliptical distributions |
| topic | Statistics Theory |
| url | https://arxiv.org/abs/2408.12131 |