Re-visiting the COVID-19 analysis using the class of high ordered integer-valued time series models with harmonic features
The COVID-19 series is obviously one of the most volatile time series with lots of spikes and oscillations. The conventional integer-valued auto-regressive time series models (INAR) may be limited to account for such features in COVID-19 series such as severe over-dispersion, excess of zeros, period...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2022-11-01
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| Series: | Healthcare Analytics |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2772442522000363 |
| _version_ | 1811178890270343168 |
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| author | Naushad Mamode Khan Ashwinee Devi Soobhug Noha Youssef Swalay Fedally Saralees Nadarajah Zaid Heetun |
| author_facet | Naushad Mamode Khan Ashwinee Devi Soobhug Noha Youssef Swalay Fedally Saralees Nadarajah Zaid Heetun |
| author_sort | Naushad Mamode Khan |
| collection | DOAJ |
| description | The COVID-19 series is obviously one of the most volatile time series with lots of spikes and oscillations. The conventional integer-valued auto-regressive time series models (INAR) may be limited to account for such features in COVID-19 series such as severe over-dispersion, excess of zeros, periodicity, harmonic shapes and oscillations. This paper proposes alternative formulations of the classical INAR process by considering the class of high-ordered INAR models with harmonic innovation distributions. Interestingly, the paper further explores the bivariate extension of these high-ordered INARs. South Africa and Mauritius’ COVID-19 series are re-scrutinized under the optic of these new INAR processes. Some simulation experiments are also executed to validate the new models and their estimation procedures. |
| first_indexed | 2024-04-11T06:25:36Z |
| format | Article |
| id | doaj.art-d45719b201fa4d8fa774387227e8ee72 |
| institution | Directory Open Access Journal |
| issn | 2772-4425 |
| language | English |
| last_indexed | 2024-04-11T06:25:36Z |
| publishDate | 2022-11-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Healthcare Analytics |
| spelling | doaj.art-d45719b201fa4d8fa774387227e8ee722022-12-22T04:40:23ZengElsevierHealthcare Analytics2772-44252022-11-012100086Re-visiting the COVID-19 analysis using the class of high ordered integer-valued time series models with harmonic featuresNaushad Mamode Khan0Ashwinee Devi Soobhug1Noha Youssef2Swalay Fedally3Saralees Nadarajah4Zaid Heetun5Faculty of Social Sciences and Humanities, University of Mauritius, Réduit, MauritiusStatistics Mauritius, Ministry of Finance, Economic Planning and Development, Port-Louis, Mauritius; Corresponding author.American University of Egypt, Cairo, EgyptMinistry of Health and Wellness, Port-Louis, MauritiusDepartment of Mathematics, University of Manchester, Manchester, United KingdomMinistry of Health and Wellness, Port-Louis, MauritiusThe COVID-19 series is obviously one of the most volatile time series with lots of spikes and oscillations. The conventional integer-valued auto-regressive time series models (INAR) may be limited to account for such features in COVID-19 series such as severe over-dispersion, excess of zeros, periodicity, harmonic shapes and oscillations. This paper proposes alternative formulations of the classical INAR process by considering the class of high-ordered INAR models with harmonic innovation distributions. Interestingly, the paper further explores the bivariate extension of these high-ordered INARs. South Africa and Mauritius’ COVID-19 series are re-scrutinized under the optic of these new INAR processes. Some simulation experiments are also executed to validate the new models and their estimation procedures.http://www.sciencedirect.com/science/article/pii/S2772442522000363COVID-19 deathsHarmonic innovationsINAR(p)SimulationEstimation |
| spellingShingle | Naushad Mamode Khan Ashwinee Devi Soobhug Noha Youssef Swalay Fedally Saralees Nadarajah Zaid Heetun Re-visiting the COVID-19 analysis using the class of high ordered integer-valued time series models with harmonic features Healthcare Analytics COVID-19 deaths Harmonic innovations INAR(p) Simulation Estimation |
| title | Re-visiting the COVID-19 analysis using the class of high ordered integer-valued time series models with harmonic features |
| title_full | Re-visiting the COVID-19 analysis using the class of high ordered integer-valued time series models with harmonic features |
| title_fullStr | Re-visiting the COVID-19 analysis using the class of high ordered integer-valued time series models with harmonic features |
| title_full_unstemmed | Re-visiting the COVID-19 analysis using the class of high ordered integer-valued time series models with harmonic features |
| title_short | Re-visiting the COVID-19 analysis using the class of high ordered integer-valued time series models with harmonic features |
| title_sort | re visiting the covid 19 analysis using the class of high ordered integer valued time series models with harmonic features |
| topic | COVID-19 deaths Harmonic innovations INAR(p) Simulation Estimation |
| url | http://www.sciencedirect.com/science/article/pii/S2772442522000363 |
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