The Beta Generalized Inverted Exponential Distribution with Real Data Applications

Abstract

The four-parameter beta generalized inverted exponential distribution is considered in this article. Various properties of the model with graphs of the density function are investigated. Moreover, the maximum likelihood method of estimation is used for estimating the parameters of the model under complete samples. An asymptotic Fisher information matrix of the estimators is found. Additionally, confidence interval estimates of the parameters are obtained. The performances of findings of the article are shown by demonstrating various numerical illustrations through Monte Carlo simulation studies. Finally, applications on real data-sets are provided.