AIP Advances (Mar 2024)

A new flexible distribution: Statistical inference with application

  • Muhammad Ahsan-ul-Haq,
  • Muhammad Umar Farooq,
  • M. Nagy,
  • A. H. Mansi,
  • Alexis Habineza,
  • Waleed Marzouk

DOI
https://doi.org/10.1063/5.0189404
Journal volume & issue
Vol. 14, no. 3
pp. 035030 – 035030-12

Abstract

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A flexible distribution for the analysis of bounded data is proposed. The new model is generalized through the transmuted approach, and the resultant model is named “transmuted modified Lehmann-type II distribution.” A comprehensive analysis of key characteristics is performed, including the shape of the model, survival, and hazard function, analytical expressions of mode, quantile function, ordinary moments, quantile function, and stress–strength reliability. Some famous entropy measures are also derived. The model parameters have been estimated using four distinct methods, including maximum likelihood estimation, Anderson Darling, Cramer–von Misses, and ordinary least squares. A detailed simulation study is used to evaluate the behavior of all derived estimators. Finally, a dataset was used to demonstrate the utility of the proposed distribution.