Inverse Exponentiated Lomax Power Series Distribution: Model, Estimation, and Application

In this paper, we introduce the inverse exponentiated Lomax power series (IELoPS) class of distributions, obtained by compounding and distributions. The IELoPS contains some significant new flexible lifetime distributions that possess powerful physical explications applied in areas like industrial biological studies. comprises as a subclass well several compounded For proposed class, characteristics properties are derived such hazard rate function, limiting behavior, quantile Lorenz Bonferroni curves, mean residual life, inactivity time, measures information. methods maximum likelihood Bayesian estimations used to estimate model parameters one optional model. estimators discussed under squared error linear exponential loss functions. asymptotic confidence intervals, credible parameters, constructed. Simulations for one-selective model, say Poisson (IELoP) distribution, designed assess compare different estimates. Results study emphasized merit produced addition, they appeared superiority regarded priors compared corresponding estimate. Finally, examine medical reliability data demonstrate applicability, flexibility, usefulness IELoP distribution. suggested two real sets, distribution fits better than Kumaraswamy–Weibull, Poisson–Lomax, Lomax, Weibull–Lomax, Gumbel–Lomax, odd Burr–Weibull–Poisson, Lomax–Poisson