Numerical computation of the Rosenblatt distribution and applications
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arXiv
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866908427724259328 |
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| author | Leonenko, Nikolai N. Pepelyshev, Andrey |
| author_facet | Leonenko, Nikolai N. Pepelyshev, Andrey |
| contents | The Rosenblatt distribution plays a key role in the limit theorems for non-linear functionals of stationary Gaussian processes with long-range dependence. We derive new expressions for the characteristic function of the Rosenblatt distribution. Also we present a novel accurate approximation of all eigenvalues of the Riesz integral operator associated with the correlation function of the Gaussian process and propose an efficient algorithm for computation of the density of the Rosenblatt distribution. We perform Monte-Carlo simulation for small sample sizes to demonstrate the appearance of the Rosenblatt distribution for several functionals of stationary Gaussian processes with long-range dependence. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_23337 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Numerical computation of the Rosenblatt distribution and applications Leonenko, Nikolai N. Pepelyshev, Andrey Statistics Theory The Rosenblatt distribution plays a key role in the limit theorems for non-linear functionals of stationary Gaussian processes with long-range dependence. We derive new expressions for the characteristic function of the Rosenblatt distribution. Also we present a novel accurate approximation of all eigenvalues of the Riesz integral operator associated with the correlation function of the Gaussian process and propose an efficient algorithm for computation of the density of the Rosenblatt distribution. We perform Monte-Carlo simulation for small sample sizes to demonstrate the appearance of the Rosenblatt distribution for several functionals of stationary Gaussian processes with long-range dependence. |
| title | Numerical computation of the Rosenblatt distribution and applications |
| topic | Statistics Theory |
| url | https://arxiv.org/abs/2506.23337 |