A New Extension of the Inverse Power Lomax Distribution

Abstract

In this article, we propose a new extension of the inverse power Lomax distribution that takes advantage of the functionalities of the sine transformation. It is called the sine inverse power Lomax (SIPL) distribution. In the first part, its primary characteristics are first identified. The heavy-tailed nature of the SIPL distribution, as well as the versatility of its distribution functions, are emphasized.
Also, among other things, we prove some first-order stochastic dominance structures and derive expressions for the quantile function, diverse moments, and income curves. Subsequently, the predictive ability of the SIPL model is investigated. A maximum likelihood calculation technique is used to estimate the parameters of the model, and simulations are run to verify its effectiveness. Then, two actual data sets are considered for analysis. When the SIPL model is compared to other Lomax-type models, it comes first according to standard statistical metrics.

Key words and phrases. Inverse power Lomax distribution, sine formed family, moments, income curves, estimation.

2010 Mathematics Subject Classification. 60E05; 62F10