Confluent hypergeometric inverse exponential distribution with application to climate and economic data

This paper presents the confluent hypergeometric version of the inverse exponential distribution. The model has emphasized for its exceptional versatility and efficiency in modelling various data types, especially data with high-kurtosis. It supports a wide range of distribution shapes, such as unimodal, reverse J-shaped, right-skewed, and asymmetrical. The essential mathematical properties and characteristics of the model are derived. Parameter estimation is carried out using the maximum likelihood estimation technique with simulation study. The main purpose of this study is to develop a distribution to model asymmetrically characterized variables to aid climate scientists with an effective tool to analyse and study the rainfall data. Furthermore, the analysis also showed that the Confluent hypergeometric inverse exponential distribution can effectively model asymmetrically characterized economic variables (income data) also.