Abstract

This research paper aims to find the estimated values closest to the true values of the reliability function under lower record values, and to know how to obtain these estimated values using point estimation methods or interval estimation methods. This helps researchers later in obtaining values of the reliability function in theory and then applying them to reality which makes it easier for the researcher to access the missing data for long periods such as weather. We evaluated the stress-strength model of reliability based on point and interval estimation for reliability under lower records by using Odd Generalize Exponential-Exponential distribution (OGEE) which has an important role in the lifetime of data. After that, we compared the estimated values of reliability with the real values of it. We analyzed the data obtained by the simulation method and the real data in order to reach certain results. The Numerical results for estimated values of reliability supported with graphical illustrations. The results of both simulated data and real data gave us the same coverage.

Highlights

  • The lower record values have an important role in solving a lot of problems that concern the studying of missing data for long periods, for example, weather, phenomenon, and health care studies

  • In this article, the maximum likelihood estimate (MLE) and Bayes estimators were computed to stress - strength reliability function when both the stress and the strength have GEE distributions based on lower record values

  • Overview of the estimated results obtained in the previous tables in which we find that the percentage of convergence for MLE is better than the percentage of affinity for Bayes

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Summary

Introduction

The lower record values have an important role in solving a lot of problems that concern the studying of missing data for long periods, for example, weather, phenomenon, and health care studies. The statistical study of lower record was introduced. For Bayesian comparison of record values based on generalized exponential distribution were considered in [2]. Authors found Bayesian analysis for record data Based on Generalized Inverted Exponential Model which considered in [3]. For finding interval estimation for Inverse Rayleigh Distribution based on lower record see [4]. For estimating the reliability for a family of life time distribution based on records see [5]. In [6] they estimated reliability for burr distribution in case of record data. For general class of distribution [7] studied the reliability with lower record. In [8] they found UMVUE of reliability in case of record values and the data has proportional reversed hazard family

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