Classical and Bayesian inference for the new four-parameter Lomax distribution with applications

被引:1
作者
Abdullah, Mahreen [1 ]
Ahsan-ul-Haq, Muhammad [2 ]
Alomair, Abdullah M. [3 ]
Alomair, Mohammed A. [3 ]
机构
[1] Minhaj Univ Lahore, Sch Stat, Lahore, Pakistan
[2] Univ Punjab, Coll Stat Sci, Lahore, Pakistan
[3] King Faisal Univ, Sch Business, Dept Quantitat Methods, Al Hasa 31982, Saudi Arabia
关键词
Generalization; power Lomax; Moments; Metropolis -Hasting 's algorithm; Inference; Data analysis; G FAMILY;
D O I
10.1016/j.heliyon.2024.e25842
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
In this study, a new four-parameter Lomax distribution is proposed using a new alpha power transformation technique. The new distribution is named "New Alpha Power Transformed Power Lomax Distribution." Mathematical properties, including moments, the moment-generating function, the mean residual life, order statistics, and the quantile function, are obtained. The maximum likelihood estimation approach is used to estimate the model parameters. A comprehensive simulation is used to evaluate the behavior of maximum likelihood estimators. Two realworld data sets were used to demonstrate the significance of the proposed model, and the results show that the new model performs better when interpreting lifetime data sets. In the end, for the data sets, Bayesian estimation and Metropolis-Hasting's approach were also utilized to construct the approximate Bayes estimates, and convergence diagnostic methods based on Markov Chain Monte Carlo techniques were applied.
引用
收藏
页数:14
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