Estimating the reliability function of Kumaraswamy distribution data
DOI:
https://doi.org/10.33095/jeas.v25i115.1776Keywords:
/ توزيع Kw, طريقة (ML) , طريقة Bayes)) , متوسط مربعات الخطأ MSE)) ., Estimating the reliability function of Kumaraswamy distribution dataAbstract
The aim of this study is to estimate the parameters and reliability function for kumaraswamy distribution of this two positive parameter (a,b > 0), which is a continuous probability that has many characterstics with the beta distribution with extra advantages.
The shape of the function for this distribution and the most important characterstics are explained and estimated the two parameter (a,b) and the reliability function for this distribution by using the maximum likelihood method (MLE) and Bayes methods. simulation experiments are conducts to explain the behaviour of the estimation methods for different sizes depending on the mean squared error criterion the results show that the Bayes is better than the ML.
Downloads
Published
Issue
Section
License
Articles submitted to the journal should not have been published before in their current or substantially similar form, or be under consideration for publication with another journal. Please see JEAS originality guidelines for details. Use this in conjunction with the points below about references, before submission i.e. always attribute clearly using either indented text or quote marks as well as making use of the preferred Harvard style of formatting. Authors submitting articles for publication warrant that the work is not an infringement of any existing copyright and will indemnify the publisher against any breach of such warranty. For ease of dissemination and to ensure proper policing of use, papers and contributions become the legal copyright of the publisher unless otherwise agreed.
The editor may make use of Turnitin software for checking the originality of submissions received.
How to Cite
How to use the OJS system 
