Estimation of the Parameters of the Bivariate Generalized Exponential Distribution using Accelerated Life Testing with Censoring Data

Abstract

In this paper, the estimation for the bivariate generalized exponential (BVGE) distribution under type-I censored with constant stress accelerated life testing (CSALT) are discussed. The scale parameter of the lifetime distribution at constant stress levels is assumed to be an inverse power law function of the stress level. The unknown parameters are estimated by the maximum likelihood approach and their approximate variance-covariance matrix is obtained. Then, the numerical studies are introduced to illustrate the approach study using samples which have been generated from the bivariate generalized exponential distribution.

Bayesian estimation of the parameters of the bivariate generalized exponential distribution using accelerated life testing under censoring data

“…Lakshmi and Durgadevi [22] presented a study in the application part for the BVGE distribution. Assar and Abd El-Maseh [7] presented maximum likelihood estimation for the unknown parameters of the BVGE distribution under type-I censoring samples with accelerated life testing. Accelerated life testing (ALT) is becoming so important and widely used in many fields, such as: in manufacturing industries to assess or demonstrate component and subsystem reliability, in rapidly changing technologies, higher customer expectations for better reliability and the need for rapid device development (see Attia et al [8]).…”