Bayesian and Non-Bayesian Estimation Methods for Simulating the Parameter of the Akshaya Distribution | ||||
| Computational Journal of Mathematical and Statistical Sciences | ||||
| Article 2, Volume 1, Issue 1, November 2022, Page 13-25 PDF (369.4 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/cjmss.2022.270897 | ||||
 View on SCiNiTO | ||||
| Author | ||||
Ahlam. H. Tolba 
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| Department of Mathematics, Faculty of Science, Mansoura University, Mansoura 33516, Egypt | ||||
| Abstract | ||||
| The ”Akshaya distribution” is a model one-parameter continuous distribution that has been proposed by [15] for modelling lifetime data from biological research and engineering. This paper presents both the classical and Bayesian estimation methods for the Akshaya’s parameter. The model parameter is determined using the weighted least square estimation (WLSE), least square estimation(LSE), Cramer-von-Mises estimation(CVME), and maximum likelihood estimation (MLE), five conventional estimation methods. Additionally, the squared error loss function and Bayesian estimation(BE) under independent gamma priors were used to determine the parameter of the proposed distribution. Finally, the applicability and utility of the proposed distribution is elaborated using simulation study. | ||||
| Keywords | ||||
| Akshaya distribution; Bayesian procedure; maximum likelihood estimation; Anderson-Darling estimation; Cramer-von-Mises estimation least square estimation; Weighted least square estimation | ||||
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