Dealing with Outliers in ARMA Time Series Analysis Using Hampel Filter and Wavelet Analysis

Outliers affect the accuracy of the estimated parameters of ARMA time series models which can be handled by the Hampel filter. In this article, wavelet shrinkage is proposed to handle outliers of ARMA models by using wavelet (Daubechies for order 4, Symlets for order 1, and Dmey) with a universal th...

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Main Author: Heyam Abd Al-Majeed Hayawi
Format: Article
Language:English
Published: Mosul University 2025-06-01
Series:Al-Rafidain Journal of Computer Sciences and Mathematics
Subjects:
Online Access:https://csmj.uomosul.edu.iq/article_187528_69041554815d8731011ada81c931dc9b.pdf
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author Heyam Abd Al-Majeed Hayawi
author_facet Heyam Abd Al-Majeed Hayawi
author_sort Heyam Abd Al-Majeed Hayawi
collection DOAJ
description Outliers affect the accuracy of the estimated parameters of ARMA time series models which can be handled by the Hampel filter. In this article, wavelet shrinkage is proposed to handle outliers of ARMA models by using wavelet (Daubechies for order 4, Symlets for order 1, and Dmey) with a universal threshold method and applying a soft threshold. To compare the efficiency of the proposed method and the traditional method (Hampel filter), the mean square error, Akaike and Bayes information criteria were calculated for simulated and real data (The wind speed series data). The proposed method addresses the problem of outliers and provides estimated parameters for ARMA models with higher efficiency than the traditional method.
format Article
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institution Kabale University
issn 1815-4816
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language English
publishDate 2025-06-01
publisher Mosul University
record_format Article
series Al-Rafidain Journal of Computer Sciences and Mathematics
spelling doaj-art-eb27452cabf4472c913e08684e3fa32c2025-08-20T04:00:44ZengMosul UniversityAl-Rafidain Journal of Computer Sciences and Mathematics1815-48162311-79902025-06-0119111312110.33899/csmj.2025.157319.1173187528Dealing with Outliers in ARMA Time Series Analysis Using Hampel Filter and Wavelet AnalysisHeyam Abd Al-Majeed Hayawi0Department of Statistics and Informatics, College of Computer Science and Mathematics, University of Mosul,Mosul,IraqOutliers affect the accuracy of the estimated parameters of ARMA time series models which can be handled by the Hampel filter. In this article, wavelet shrinkage is proposed to handle outliers of ARMA models by using wavelet (Daubechies for order 4, Symlets for order 1, and Dmey) with a universal threshold method and applying a soft threshold. To compare the efficiency of the proposed method and the traditional method (Hampel filter), the mean square error, Akaike and Bayes information criteria were calculated for simulated and real data (The wind speed series data). The proposed method addresses the problem of outliers and provides estimated parameters for ARMA models with higher efficiency than the traditional method.https://csmj.uomosul.edu.iq/article_187528_69041554815d8731011ada81c931dc9b.pdftime seriesarma modeloutliershampel filterand wavelets
spellingShingle Heyam Abd Al-Majeed Hayawi
Dealing with Outliers in ARMA Time Series Analysis Using Hampel Filter and Wavelet Analysis
Al-Rafidain Journal of Computer Sciences and Mathematics
time series
arma model
outliers
hampel filter
and wavelets
title Dealing with Outliers in ARMA Time Series Analysis Using Hampel Filter and Wavelet Analysis
title_full Dealing with Outliers in ARMA Time Series Analysis Using Hampel Filter and Wavelet Analysis
title_fullStr Dealing with Outliers in ARMA Time Series Analysis Using Hampel Filter and Wavelet Analysis
title_full_unstemmed Dealing with Outliers in ARMA Time Series Analysis Using Hampel Filter and Wavelet Analysis
title_short Dealing with Outliers in ARMA Time Series Analysis Using Hampel Filter and Wavelet Analysis
title_sort dealing with outliers in arma time series analysis using hampel filter and wavelet analysis
topic time series
arma model
outliers
hampel filter
and wavelets
url https://csmj.uomosul.edu.iq/article_187528_69041554815d8731011ada81c931dc9b.pdf
work_keys_str_mv AT heyamabdalmajeedhayawi dealingwithoutliersinarmatimeseriesanalysisusinghampelfilterandwaveletanalysis