International Journal of Statistics and Applied Mathematics
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International Journal of Statistics and Applied Mathematics

2021, Vol. 6, Issue 5, Part B

Inference for the generalized inverse Lindley distribution under type-II censored data


Author(s): Hora Rashi, Kabdwal Naresh and Srivastava Pulkit

Abstract: In this paper, we consider the classical and the Bayesian inferences for the generalized inverse Lindley (GIL) distribution and their corresponding reliability characteristics (reliability function and hazard rate function) under the type-II censoring scheme. In the classical setup, first we obtain the maximum likelihood estimator for the unknown parameters of the distribution and their corresponding reliability characteristics. Further, we consider symmetric (squared error) and asymmetric (LINEX and general entropy) loss functions for the estimation of parameters and their corresponding reliability characteristics under the Bayesian paradigm. The performances of various derived estimators were recorded using Markov chain Monte Carlo (MCMC) simulation technique in Open BUGS for different sample sizes under type-II censoring schemes. Finally, a real data set is provided to illustrate the computation of various estimators.

DOI: 10.22271/maths.2021.v6.i5b.739

Pages: 155-166 | Views: 20 | Downloads: 5

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How to cite this article:
Hora Rashi, Kabdwal Naresh, Srivastava Pulkit. Inference for the generalized inverse Lindley distribution under type-II censored data. Int J Stat Appl Math 2021;6(5):155-166. DOI: 10.22271/maths.2021.v6.i5b.739
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