Nonparametric two sample test of spectral densities
Fuente:
arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2026
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| _version_ | 1866912897238564864 |
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| author | Nadin, Ilaria Krivobokova, Tatyana Enikeeva, Farida |
| author_facet | Nadin, Ilaria Krivobokova, Tatyana Enikeeva, Farida |
| contents | A novel nonparametric test for the equality of the covariance matrices of two Gaussian stationary processes, possibly of different lengths, is proposed. The test translates to testing the equality of two spectral densities and is shown to be minimax rate-optimal. Test performance is validated in a simulation study, and the practical utility is demonstrated in the analysis of real electroencephalography data. The test is implemented in the R-package sdf.test. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_10774 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Nonparametric two sample test of spectral densities Nadin, Ilaria Krivobokova, Tatyana Enikeeva, Farida Statistics Theory A novel nonparametric test for the equality of the covariance matrices of two Gaussian stationary processes, possibly of different lengths, is proposed. The test translates to testing the equality of two spectral densities and is shown to be minimax rate-optimal. Test performance is validated in a simulation study, and the practical utility is demonstrated in the analysis of real electroencephalography data. The test is implemented in the R-package sdf.test. |
| title | Nonparametric two sample test of spectral densities |
| topic | Statistics Theory |
| url | https://arxiv.org/abs/2602.10774 |