Inference on Generalized Inverse Lindley Distribution under Progressive Hybrid Censoring Scheme

Document Type : Original Article

Authors
Suparna Basu 1
Sanjay K. Singh 2
Umesh Singh 3
1 Dept. of Statistics, MMV, Banaras Hindu University
2 Dept. of Statistics, Institute of Science, Banaras Hindu University
3 Department of Statistics, Institute of Science, Banaras Hindu University
10.22034/jirss.2022.707643
Abstract
This article delineates the implementation of the product of spacings under Progressive Hybrid Type-I censoring with binomial removals for the Generalized Inverse Lindley distribution. Both point and interval estimates of the parameters have been obtained under classical as well as Bayesian paradigms using the product of spacings. The proposed estimators can be used in lieu of maximum likelihood as well as usual Bayes estimator based on likelihood function which is corroborated by a comparative simulation study. The Bayesian estimation is performed under the assumption of squared error loss function. The implicit integrals involved in the process are evaluated using Metropolis-Hastings algorithm within Gibbs sampler. We have also derived the expected total time to test statistic for the specified censoring scheme. The applicability of the proposed methodology is demonstrated by analyzing a real data set of active repair times for an airborne communication transceiver.
Keywords
Maximum Product of Spacing
Progressive Hybrid Type-I Censoring with Binomial Removals
Expected Total Time to Test
Gibbs Sampler Algorithm
Subjects
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Journal of the Iranian Statistical Society
Volume 21, Issue 2
December 2022
Pages 21-50

  • Receive Date 24 September 2021
  • Revise Date 11 July 2023
  • Accept Date 15 September 2023