Bayes estimators for reliability and hazard function of Rayleigh-Logarithmic (RL) distribution with application
DOI:
https://doi.org/10.21533/pen.v8.i4.1366Abstract
In this paper, we derived an estimators and parameters of Reliability and Hazard function of new mix
distribution ( Rayleigh- Logarithmic) with two parameters and increasing failure rate using Bayes Method
with Square Error Loss function and Jeffery and conditional probability random variable of observation. The
main objective of this study is to find the efficiency of the derived of Bayesian estimator compared to the
to the Maximum Likelihood of this function using Simulation technique by Monte Carlo method under
different Rayleigh- Logarithmic parameter and sample sizes. The consequences have shown that Bayes
estimator has been more efficient than the maximum likelihood estimator in all sample sizes with application.
Downloads
Published
Issue
Section
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
