QUANTILE MOMENT ESTIMATION OF NEW ALPHA POWER WEIBULL FOR BANK ASSISTANCE WAITING TIME

Abstract

The paradigm of the New Alpha power transformation, which is an original and effective strategy, was used to build the New Generalized Alpha Inverse Weibull (NAPIW) distribution, which exhibits spectacular statistical properties and has useful applications. In this paper, the classification of the NAPIW distribution is thoroughly investigated, and the basic statistical properties, such as dependability and moments, are addressed in detail. The NAPIW distribution’s behavior can only be understood with the help of this information. The Linear Quantile Moment method and the Maximum Likelihood Estimation approach are both utilized to streamline practical implementations for precise parameter estimation of the NAPIW distribution. The efficacy of the proposed distribution is demonstrated through its successful application to real-world data, specifically the analysis of customer waiting times in a bank, as well as simulations, underscoring its suitability for modeling diverse datasets. Additionally, comprehensive assessments, including mean square errors for all parameters and other relevant measurements, are performed, validating the superior performance of the NAPIW distribution over existing models, and establishing it as a robust and versatile tool for researchers and practitioners in various fields.

keywords: Alpha Inverse Weibull, Linear Quantile Moment, Reliability,Inactivity time.