Abstract
As researchers are increasingly interested in natural disasters and economic problems, developing solutions to predict that is highly recommended. In this paper, we focus on the use of the Extreme Values Theory (EVT) especially the Gumbel distribution, for modelling and predicting the maximum data of extreme events in a time series. To achieve this goal, first we have to demonstrate that the time series formed by the maximum values converges to the Gumbel distribution. Then by applying several fitting methods such as the method of mayer, the method of moments and finally the method of least squares, we are able to estimate the Gumbel parameters to be used for prediction. The performance of the fitting methods was tested using specific measures of accuracy.
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Mateur, A., Khabou, N., Bouassida Rodriguez, I. (2022). How to Automatically Prove a Time Series Convergence to the Gumbel Distribution?. In: Barolli, L., Hussain, F., Enokido, T. (eds) Advanced Information Networking and Applications. AINA 2022. Lecture Notes in Networks and Systems, vol 449. Springer, Cham. https://doi.org/10.1007/978-3-030-99584-3_31
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DOI: https://doi.org/10.1007/978-3-030-99584-3_31
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