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Estimating the Parameters of the Generalized Inverted Kumaraswamy Distribution through the Utilization of a First Failure-Censored Sampling Plan |
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PP: 1251-1261 |
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doi:10.18576/jsap/130410
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Author(s) |
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M. Yusuf,
H. M. Barakat,
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Abstract |
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| This paper focuses on the development of approximate Bayes estimators for the shape parameters of the generalized inverted Kumaraswamy (GIKum) distribution. The estimators are based on a progressive first-failure censored plan. The study considers both maximum likelihood and Bayesian estimations using a gamma-informative prior distribution for the parameters, as well as the reliability function, hazard rate, and reversed hazard rate functions. To obtain the estimators, the paper employs Lindley’s approximation and utilizes Markov Chain Monte Carlo (MCMC) methods. The Bayes estimators are derived with respect to both symmetric (squared error) and asymmetric (linex and general entropy) loss functions. In order to assess the performance of the proposed estimators, the paper presents numerical results obtained through a simulation study involving different sample sizes.
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