Summary: | The objective of the study is to use quantile regression to estimate extreme value events. The exploration of extreme value events requires the use of heavy-tailed distributions to build a model which fits the data well. One needs to estimate high conditional quantiles of a random variable for extreme events. Quantile regression ultimately yields results which the alternative mean regression method has no hope to offer, leading to it being labeled as the more powerful method. In order to improve this approach even further, a weighted quantile regression method is introduced with a complete comparison to the unweighted method. The Monte Carlo simulations show good results for the proposed weighted method. Comparisons of the proposed method and existing methods are given. The paper also investigates two real-world examples of applications on extreme events using the proposed weighted method.
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