A note on wavelet shrinkage in nonparametric regression models with ARFIMA errors

Fuente: arXiv
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Main Authors: Sousa, Alex Rodrigo dos S., Zevallos, Mauricio
Format: Preprint
Published: 2025
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author Sousa, Alex Rodrigo dos S.
Zevallos, Mauricio
author_facet Sousa, Alex Rodrigo dos S.
Zevallos, Mauricio
contents In this paper we propose a shrinkage wavelet-based method to estimate the signal in a nonparametric regression model with Autoregressive Fractionally Integrated Moving Average (ARFIMA) errors. Monte Carlo experiments indicate that the proposed method is better than the universal thresholding rule which is widely used in data analysis via wavelet regression models.
format Preprint
id arxiv_https___arxiv_org_abs_2505_06485
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle A note on wavelet shrinkage in nonparametric regression models with ARFIMA errors
Sousa, Alex Rodrigo dos S.
Zevallos, Mauricio
Methodology
In this paper we propose a shrinkage wavelet-based method to estimate the signal in a nonparametric regression model with Autoregressive Fractionally Integrated Moving Average (ARFIMA) errors. Monte Carlo experiments indicate that the proposed method is better than the universal thresholding rule which is widely used in data analysis via wavelet regression models.
title A note on wavelet shrinkage in nonparametric regression models with ARFIMA errors
topic Methodology
url https://arxiv.org/abs/2505.06485