Asymptotic analysis of the finite predictor for the fractional Gaussian noise
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arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866909561398493184 |
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| author | Chigansky, P. Kleptsyna, M. |
| author_facet | Chigansky, P. Kleptsyna, M. |
| contents | The goal of this paper is to propose a new approach to asymptotic analysis of the finite predictor for stationary sequences. It produces the exact asymptotics of the relative prediction error and the partial correlation coefficients. The assumptions are analytic in nature and applicable to processes with long range dependence. The ARIMA type process driven by the fractional Gaussian noise (fGn), which previously remained elusive, serves as our study case. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2504_01562 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Asymptotic analysis of the finite predictor for the fractional Gaussian noise Chigansky, P. Kleptsyna, M. Statistics Theory Probability The goal of this paper is to propose a new approach to asymptotic analysis of the finite predictor for stationary sequences. It produces the exact asymptotics of the relative prediction error and the partial correlation coefficients. The assumptions are analytic in nature and applicable to processes with long range dependence. The ARIMA type process driven by the fractional Gaussian noise (fGn), which previously remained elusive, serves as our study case. |
| title | Asymptotic analysis of the finite predictor for the fractional Gaussian noise |
| topic | Statistics Theory Probability |
| url | https://arxiv.org/abs/2504.01562 |