Volume 3, Issue 1 (6-2022)                   MACO 2022, 3(1): 61-71 | Back to browse issues page


XML Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Jabbari Nooghabi M, Soori A, Nasiri P, Hormozinejad F, Ghalani M. Objective Bayesian Analysis For a Two-parameters Exponential Distribution. MACO 2022; 3 (1) :61-71
URL: http://maco.lu.ac.ir/article-1-103-en.html
Abstract:   (983 Views)
In any Bayesian inference problem, the posterior distribution is a product of the
likelihood and the prior: thus, it is a ected by both in cases where one possesses little or no
information about the target parameters in advance. In the case of an objective Bayesian
analysis, the resulting posterior should be expected to be universally agreed upon by ev-
eryone, whereas . subjective Bayesianism would argue that probability corresponds to the
degree of personal belief. In this paper, we consider Bayesian estimation of two-parameter
exponential distribution using the Bayes approach needs a prior distribution for parame-
ters. However, it is dicult to use the joint prior distributions. Sometimes, by using linear
transformation of reliability function of two-parameter exponential distribution in order to
get simple linear regression model to estimation of parameters. Here, we propose to make
Bayesian inferences for the parameters using non-informative priors, namely the (depen-
dent and independent) Je reys' prior and the reference prior. The Bayesian estimation was
assessed using the Monte Carlo method. The criteria mean square error was determined
evaluate the possible impact of prior speci cation on estimation. Finally, an application on
a real dataset illustrated the developed procedures.
Full-Text [PDF 139 kb]   (787 Downloads)    
Type of Study: Research Article | Subject: Applied Mathematics
Published: 2022/07/24

Send email to the article author


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.