A New Generalisation of the Quasi-Rama Distribution: Exploring its Statistical Properties and Applications

Abstract

The concept of a weighted distribution is applicable for adjusting the probabilities of events, and biased data arise within this theory. The weighted distribution idea was first suggested by Fisher (1934) to modify ascertainment biases. Weighted distributions provide a comprehensive technique to extend the existing baseline distribution by incorporating additional parameters, thereby enhancing the capability of the existing distribution.  In this paper, a new version of the quasi-Rama distribution, referred to as the weighted quasi-Rama distribution, is proposed by applying the weighted technique to the baseline quasi-Rama distribution. The new distribution is explored through several structural features. Maximum Likelihood method is employed to estimate the model parameters. By using the real dataset, the superiority and capability of the proposed distribution have been demonstrated and assessed.