(2007). Estimation of the Generalized Exponential Distribution Parameters Under Constant-Stress Partially Accelerated Life Testing Using Type I Censoring. The Egyptian Statistical Journal, 51(2), 48-62. doi: 10.21608/esju.2007.313449
. "Estimation of the Generalized Exponential Distribution Parameters Under Constant-Stress Partially Accelerated Life Testing Using Type I Censoring". The Egyptian Statistical Journal, 51, 2, 2007, 48-62. doi: 10.21608/esju.2007.313449
(2007). 'Estimation of the Generalized Exponential Distribution Parameters Under Constant-Stress Partially Accelerated Life Testing Using Type I Censoring', The Egyptian Statistical Journal, 51(2), pp. 48-62. doi: 10.21608/esju.2007.313449
Estimation of the Generalized Exponential Distribution Parameters Under Constant-Stress Partially Accelerated Life Testing Using Type I Censoring. The Egyptian Statistical Journal, 2007; 51(2): 48-62. doi: 10.21608/esju.2007.313449
Estimation of the Generalized Exponential Distribution Parameters Under Constant-Stress Partially Accelerated Life Testing Using Type I Censoring
Testing the lifetime of items under normal use condition often requires a long period of time, particularly for a product having high reliability. To minimize the costs involved in testing without reducing the quality of the data obtained, the items run at higher than usual level of stresses to induce early failure. This article concerns with constant-stress partially accelerated life tests (CS-PALT) based on type I censoring in which each test item is observed until it fails before a predetermined time, keeping all the stress factors at constant level. The lifetime of items is assumed to follow generalized exponential distribution. Maximum likelihood method is used to estimate the model parameters and acceleration factor of lifetime distribution from the test data. Netwon Raphson method is applied to solve numerically the non-linear likelihood equations using Mathcad (2001). Confidence intervals of the estimators are constructing. In addition, an asymptotic variance and covariance matrix of the estimators is obtained. Simulation studies are carried out to investigate the performance of the estimators.
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