Modeling Nigerian Covid-19 cases: A comparative analysis of models and estimators. (September 2020)
- Record Type:
- Journal Article
- Title:
- Modeling Nigerian Covid-19 cases: A comparative analysis of models and estimators. (September 2020)
- Main Title:
- Modeling Nigerian Covid-19 cases: A comparative analysis of models and estimators
- Authors:
- Ayinde, Kayode
Lukman, Adewale F.
Rauf, Rauf I.
Alabi, Olusegun O.
Okon, Charles E.
Ayinde, Opeyemi E. - Abstract:
- Highlights: COVID-19 remains a major pandemic currently facing all the countries of the world, Nigeria inclusive. We build some statistical model to the available data. We choose the best model to make some forecast. Abstract: COVID-19 remains a major pandemic currently threatening all the countries of the world. In Nigeria, there were 1, 932 COVID-19 confirmed cases, 319 discharged cases and 58 deaths as of 30th April 2020. This paper, therefore, subjected the daily cumulative reported COVID-19 cases of these three variables to nine (9) curve estimation statistical models in simple, quadratic, cubic, and quartic forms. It further identified the best of the thirty-six (36) models and used the same for prediction and forecasting purposes. The data collected by the Nigeria Centre for Disease Control for sixty-four (64) days, two (2) months and three (3), were daily monitored and eventually analyzed. We identified the best models to be Quartic Linear Regression Model with an autocorrelated error of order 1 (AR(1)); and found the Ordinary Least Squares, Cochrane Orcutt, Hildreth–Lu, and Prais-Winsten and Least Absolute Deviation (LAD) estimators useful to estimate the models' parameters. Consequently, we recommended the daily cumulative forecast values of the LAD estimator for May and June 2020 with a 99% confidence level. The forecast values are alarming, and so, the Nigerian Government needs to hastily review her activities and interventions towards COVID-19 to provide someHighlights: COVID-19 remains a major pandemic currently facing all the countries of the world, Nigeria inclusive. We build some statistical model to the available data. We choose the best model to make some forecast. Abstract: COVID-19 remains a major pandemic currently threatening all the countries of the world. In Nigeria, there were 1, 932 COVID-19 confirmed cases, 319 discharged cases and 58 deaths as of 30th April 2020. This paper, therefore, subjected the daily cumulative reported COVID-19 cases of these three variables to nine (9) curve estimation statistical models in simple, quadratic, cubic, and quartic forms. It further identified the best of the thirty-six (36) models and used the same for prediction and forecasting purposes. The data collected by the Nigeria Centre for Disease Control for sixty-four (64) days, two (2) months and three (3), were daily monitored and eventually analyzed. We identified the best models to be Quartic Linear Regression Model with an autocorrelated error of order 1 (AR(1)); and found the Ordinary Least Squares, Cochrane Orcutt, Hildreth–Lu, and Prais-Winsten and Least Absolute Deviation (LAD) estimators useful to estimate the models' parameters. Consequently, we recommended the daily cumulative forecast values of the LAD estimator for May and June 2020 with a 99% confidence level. The forecast values are alarming, and so, the Nigerian Government needs to hastily review her activities and interventions towards COVID-19 to provide some tactical and robust structures and measures to avert these challenges. … (more)
- Is Part Of:
- Chaos, solitons and fractals. Volume 138(2020)
- Journal:
- Chaos, solitons and fractals
- Issue:
- Volume 138(2020)
- Issue Display:
- Volume 138, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 138
- Issue:
- 2020
- Issue Sort Value:
- 2020-0138-2020-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-09
- Subjects:
- COVID-19 -- Curve Estimation Statistical Models -- Quartic Linear Regression Model -- Estimators -- Forecast Values
Chaotic behavior in systems -- Periodicals
Solitons -- Periodicals
Fractals -- Periodicals
Chaotic behavior in systems
Fractals
Solitons
Periodicals
003.7 - Journal URLs:
- http://www.elsevier.com/journals ↗
http://www.sciencedirect.com/science/journal/09600779 ↗ - DOI:
- 10.1016/j.chaos.2020.109911 ↗
- Languages:
- English
- ISSNs:
- 0960-0779
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3129.716000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 13998.xml