The accelerated life testing is the key methodology of evaluating product
reliability rapidly. This paper presents statistical inference of Gompertz
distribution based on unified hybrid censored data under constant-stress
partially accelerated life test (CSPALT) model. We apply the stochastic
expectation-maximization algorithm to estimate the CSPALT parameters
and to reduce computational complexity. It is shown that the maximum
likelihood estimates exist uniquely. Asymptotic confidence intervals and
confidence intervals using bootstrap-p and bootstrap-t methods are constructed. Moreover the maximum product of spacing (MPS) and maximum a posteriori (MAP) estimates of the model parameters and accelerated factor are discussed. The performances of the various estimators of
the CSPALT parameters are compared through the simulation study. In
summary, the MAP estimates perform superior than MLEs (or MPSs) with
respect to the smallest MSE values.
CITATIONS(9):
1.
Technological Methods for Controlling the Elastic-Deformable State in Turning and Grinding Shafts of Low Stiffness Antoni Świć, Arkadiusz Gola, Olga Orynycz, Karol Tucki, Jonas Matijošius Materials
Enhancing the Fatigue of Mechanical Systems Such as Dispensers Entrenched on Generalized Life-Stress Models and Sample Sizes Seongwoo Woo, Dennis O’Neal, Yury Matvienko, Gezae Mebrahtu Applied Sciences
Influence of the Compliance of a Technological System on the Machining Accuracy of Low-Stiffness Shafts in the Grinding Process Antoni Świć, Arkadiusz Gola Materials
Comparative Study with Applications for Gompertz Models under Competing Risks and Generalized Hybrid Censoring Schemes Laila Al-Essa, Ahmed Soliman, Gamal Abd-Elmougod, Huda Alshanbari Axioms
Statistical Prediction Based on Ordered Ranked Set Sampling Using Type-II Censored Data from the Rayleigh Distribution under Progressive-Stress Accelerated Life Tests Atef Hashem, Alaa Abdel-Hamid, Ali Sajid Journal of Mathematics
Estimation for two Gompertz populations under a balanced joint progressive Type-II censoring scheme Weihua Shi, Wenhao Gui Journal of Applied Statistics
Stress-strength reliability estimation for the inverted exponentiated Rayleigh distribution under unified progressive hybrid censoring with application Sadia Anwar, Lone Ahmad, Aysha Khan, Salmeh Almutlak Electronic Research Archive
Estimations and optimal censoring schemes for the unified progressive hybrid gamma-mixed Rayleigh distribution Showkat Lone, Hanieh Panahi, Sadia Anwar, Sana Shahab Electronic Research Archive
Inference for a constant-stress model under progressive type-II censored data from the truncated normal distribution Mohamed Sief, Xinsheng Liu, El-Raheem Abd Computational Statistics
We process personal data collected when visiting the website. The function of obtaining information about users and their behavior is carried out by voluntarily entered information in forms and saving cookies in end devices. Data, including cookies, are used to provide services, improve the user experience and to analyze the traffic in accordance with the Privacy policy. Data are also collected and processed by Google Analytics tool (more).
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.