Modified exponential time series model with prediction of total COVID-19 cases in Belgium, Czech Republic, Poland and Switzerland
Wachirapond Permpoonsinsup, Rapin Sunthornwat
The coronavirus (COVID-19) pandemic affected every country worldwide. In particular, outbreaks in Belgium, the Czech Republic, Poland and Switzerland entered the second wave and was exponentially increasing between July and November, 2020. The aims of the study are: to estimate the compound growth rate, to develop a modified exponential time-series model compared with the hyperbolic time-series model, and to estimate the optimal parameters for the models based on the exponential least-squares, three selected points, partial-sums methods, and the hyperbolic least-squares for the daily COVID-19 cases in Belgium, the Czech Republic, Poland and Switzerland. The speed and spreading power of COVID-19 infections were obtained by using derivative and root-mean-squared methods, respectively. The results show that the exponential least-squares method was the most suitable for the parameter estimation. The compound growth rate of COVID-19 infection was the highest in Switzerland, and the speed and spreading power of COVID-19 infection were the highest in Poland between July and November, 2020.
Year of publication: |
2022
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Authors: | Wachirapond Permpoonsinsup ; Rapin Sunthornwat |
Published in: |
Statistics in transition : an international journal of the Polish Statistical Association and Statistics Poland. - Warszawa : GUS, ISSN 2450-0291, ZDB-ID 2235641-1. - Vol. 23.2022, 3, p. 147-165
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Subject: | COVID-19 | modified exponential time-series model | method of parameter estimation | compound growth rate | Polen | Poland | Tschechien | Czech Republic | Coronavirus | Zeitreihenanalyse | Time series analysis | Schweiz | Switzerland | Belgien | Belgium | Prognoseverfahren | Forecasting model | Schätztheorie | Estimation theory |
Saved in:
Type of publication: | Article |
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Type of publication (narrower categories): | Aufsatz in Zeitschrift ; Article in journal |
Language: | English |
Other identifiers: | 10.2478/stattrans-2022-0035 [DOI] hdl:10419/266326 [Handle] |
Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10013428856
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