Different methods of estimation for the one parameter Akash distribution

Abstract

Akash distribution is a mixture of an exponential distribution and a gamma distribution with certain mixing proportions. Although the maximum likelihood estimation method has been proposed for the Akash distribution, there is no comprehensive comparison of different methods of estimation in the literature. This study provides five different methods of estimation, such as maximum likelihood, least-squares, weighted least-squares, Anderson-Darling, and Crámer–von-Mises for Akash distribution. We consider a comprehensive Monte Carlo simulation study to compare the performances of these methods via the biases and mean-squared errors of these estimators. Also, a real data application is performed.