PLoS ONE (Jan 2022)

A new extended gumbel distribution: Properties and application.

  • Aisha Fayomi,
  • Sadaf Khan,
  • Muhammad Hussain Tahir,
  • Ali Algarni,
  • Farrukh Jamal,
  • Reman Abu-Shanab

DOI
https://doi.org/10.1371/journal.pone.0267142
Journal volume & issue
Vol. 17, no. 5
p. e0267142

Abstract

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A robust generalisation of the Gumbel distribution is proposed in this article. This family of distributions is based on the T-X paradigm. From a list of special distributions that have evolved as a result of this family, three separate models are also mentioned in this article. A linear combination of generalised exponential distributions can be used to characterise the density of a new family, which is critical in assessing some of the family's properties. The statistical features of this family are determined, including exact formulations for the quantile function, ordinary and incomplete moments, generating function, and order statistics. The model parameters are estimated using the maximum likelihood method. Further, one of the unique models has been systematically studied. Along with conventional skewness measures, MacGillivray skewness is also used to quantify the skewness measure. The new probability distribution also enables us to determine certain critical risk indicators, both numerically and graphically. We use a simulated assessment of the suggested distribution, as well as apply three real-world data sets in modelling the proposed model, in order to ensure its authenticity and superiority.