White Noise and Its Misapplications: Impacts on Time Series Model Adequacy and Forecasting
This paper contributes significantly to time series analysis by discussing the empirical properties of white noise and their implications for model selection. This paper illustrates the ways in which the standard assumptions about white noise typically fail in practice, with a special emphasis on st...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-02-01
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| Series: | Forecasting |
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| Online Access: | https://www.mdpi.com/2571-9394/7/1/8 |
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| author | Hossein Hassani Leila Marvian Mashhad Manuela Royer-Carenzi Mohammad Reza Yeganegi Nadejda Komendantova |
| author_facet | Hossein Hassani Leila Marvian Mashhad Manuela Royer-Carenzi Mohammad Reza Yeganegi Nadejda Komendantova |
| author_sort | Hossein Hassani |
| collection | DOAJ |
| description | This paper contributes significantly to time series analysis by discussing the empirical properties of white noise and their implications for model selection. This paper illustrates the ways in which the standard assumptions about white noise typically fail in practice, with a special emphasis on striking differences in sample ACF and PACF. Such findings prove particularly important when assessing model adequacy and discerning between residuals of different models, especially ARMA processes. This study addresses issues involving testing procedures, for instance, the Ljung–Box test, to select the correct time series model determined in the review. With the improvement in understanding the features of white noise, this work enhances the accuracy of modeling diagnostics toward real forecasting practice, which gives it applied value in time series analysis and signal processing. |
| format | Article |
| id | doaj-art-4fbe9927ba12460f8d2e4cdc6ccfa7d4 |
| institution | DOAJ |
| issn | 2571-9394 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Forecasting |
| spelling | doaj-art-4fbe9927ba12460f8d2e4cdc6ccfa7d42025-08-20T02:42:32ZengMDPI AGForecasting2571-93942025-02-0171810.3390/forecast7010008White Noise and Its Misapplications: Impacts on Time Series Model Adequacy and ForecastingHossein Hassani0Leila Marvian Mashhad1Manuela Royer-Carenzi2Mohammad Reza Yeganegi3Nadejda Komendantova4International Institute for Applied Systems Analysis (IIASA), 2361 Laxenburg, AustriaBig Data Lab, Imam Reza International University, Mashhad 178-436, IranI2M, Aix-Marseille Univ, CNRS, UMR 7373, Centrale Marseille, 13007 Marseille, FranceInternational Institute for Applied Systems Analysis (IIASA), 2361 Laxenburg, AustriaInternational Institute for Applied Systems Analysis (IIASA), 2361 Laxenburg, AustriaThis paper contributes significantly to time series analysis by discussing the empirical properties of white noise and their implications for model selection. This paper illustrates the ways in which the standard assumptions about white noise typically fail in practice, with a special emphasis on striking differences in sample ACF and PACF. Such findings prove particularly important when assessing model adequacy and discerning between residuals of different models, especially ARMA processes. This study addresses issues involving testing procedures, for instance, the Ljung–Box test, to select the correct time series model determined in the review. With the improvement in understanding the features of white noise, this work enhances the accuracy of modeling diagnostics toward real forecasting practice, which gives it applied value in time series analysis and signal processing.https://www.mdpi.com/2571-9394/7/1/8time series analysismodel selectionHassani ?1/2 theoremwhite noiseARMAGaussian |
| spellingShingle | Hossein Hassani Leila Marvian Mashhad Manuela Royer-Carenzi Mohammad Reza Yeganegi Nadejda Komendantova White Noise and Its Misapplications: Impacts on Time Series Model Adequacy and Forecasting Forecasting time series analysis model selection Hassani ?1/2 theorem white noise ARMA Gaussian |
| title | White Noise and Its Misapplications: Impacts on Time Series Model Adequacy and Forecasting |
| title_full | White Noise and Its Misapplications: Impacts on Time Series Model Adequacy and Forecasting |
| title_fullStr | White Noise and Its Misapplications: Impacts on Time Series Model Adequacy and Forecasting |
| title_full_unstemmed | White Noise and Its Misapplications: Impacts on Time Series Model Adequacy and Forecasting |
| title_short | White Noise and Its Misapplications: Impacts on Time Series Model Adequacy and Forecasting |
| title_sort | white noise and its misapplications impacts on time series model adequacy and forecasting |
| topic | time series analysis model selection Hassani ?1/2 theorem white noise ARMA Gaussian |
| url | https://www.mdpi.com/2571-9394/7/1/8 |
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