Abstract
AbstractThe least squares piecewise monotonic data approximation method is applied to daily Covid-19 new cases and deaths data of the UK for the period 31-01-2020 to 19-11-2021. The data demonstrate wide variation in parts and noticeable peaks over time. We are interested in estimating turning points of the data in that the fit is useful to analyzing the progress of the pandemic. An enormous number of combinations of turning points need be considered in order to find an optimal combination, but the method provides quite efficiently a global solution. Our results show the efficacy of the piecewise monotonicity method in locating optimal turning points that are significant to the Covid-19 analyses. We consider the facts that influence the choice of the number of peaks. Our analysis provided us with insights regarding the driving forces behind the turning points that the method detected, which further may be helpful to management, as part of the information on which decisions will be made.KeywordsApproximationCombinatorial problemCovid-19 pandemic dataDivided difference of first orderLeast squares fitPeakPiecewise monotonicTurning pointUnited Kingdom
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