Nonparametric two sample test of spectral densities

Fuente: arXiv
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Main Authors: Nadin, Ilaria, Krivobokova, Tatyana, Enikeeva, Farida
Format: Preprint
Published: 2026
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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