On a Sum of Two Akash Distributions: Inference and Applications

We propose a new distribution which is the sum of two independent Akash (AK) random variables with the same parameter. We refer to this distribution as the AKS distribution. We study the density and some of its properties. We derive the method of moments (MM) and the maximum likelihood (ML) estimator, along with the Fisher information. The performance of the ML estimator is evaluated through a simulation study. In addition, we present two real data applications, demonstrating in these cases the superiority of the AKS distribution compared to two other distributions.