On Generalized Inverse Pareto Family of Distributions: Properties and Applications

In this paper, we propose new families of generalized inverse Pareto distributions using the T ‐ R { Y } framework. Several choices of the distributions for the random variables T and Y give rise to generalized families of the random variable R , which in this paper is the inverse Pareto distribution. The generalized family of distributions is thus named as T ‐inverse Pareto{ Y } family. We consider the exponential, Weibull, log‐logistic, logistic, Cauchy, and extreme value distribution as potential choices for the distribution of the random variable Y . Specific members of the T ‐inverse Pareto{ Y } family exhibit symmetric, skewed to the right, skewed to the left, unimodal, or bimodal density functions. Some statistical properties of the T ‐inverse Pareto{ Y } family are investigated. The method of maximum likelihood is proposed for estimating the distribution parameters, and its performance is assessed using a simulation study. Three real data sets from different disciplines are analyzed to demonstrate the flexibility of the proposed T ‐inverse Pareto{ Y } family of distributions.