Theoretical aspects of the development of partially accelerated life testing using Bayesian estimation
Source abstract
Abstract
Abstract In this article likelihood and Bayesian estimates of partially accelerated step-stress life testing model are compared using Type-II censored data from Gompertz distribution. Maximum likelihood estimates and the posterior means under the squared error loss function using Lindley’s approximation technique are obtained. Moreover, Markov chain Monte Carlo (MCMC) point estimates and the highest posterior density credible intervals of the model parameters based on Gibbs sampling procedure are also obtained. Monte Carlo simulation studies are performed under different sizes of samples and different parameter values for comparison purpose.
Source: openaire · Quality: candidate unverified · Source record ↗
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OpenAlex topics: Insurance, Mortality, Demography, Risk Management
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