Estimation of Stress Strength Reliability of Inverse Weibull Distribution under Progressive First Failure Censoring

  • Hare Krishna Department of Statistics, Ch. Charan Singh University, Meerut-250004
  • Madhulika Dube Department of Statistics, M.D. University, Rohtak-124001
  • Renu Garg Department of Statistics, Maharshi Dayanand University, Rohtak-124001

Abstract

In this article, estimation of stress-strength reliability $\delta=P\left(Y<X\right)$ based on progressively first failure censored data from two independent inverse Weibull distributions with different shape and scale parameters is studied. Maximum likelihood estimator and asymptotic confidence interval of $\delta$ are obtained. Bayes estimator of $\delta$ under generalized entropy loss function using non-informative and gamma informative priors is derived. Also, highest posterior density credible interval of $\delta$ is constructed. Markov Chain Monte Carlo (MCMC) technique is used for Bayes computation. The performance of various estimation methods are compared by a Monte Carlo simulation study. Finally, a pair of real life data is analyzed to illustrate the proposed methods of estimation.

Published
2018-12-17
How to Cite
Krishna, H., Dube, M., & Garg, R. (2018). Estimation of Stress Strength Reliability of Inverse Weibull Distribution under Progressive First Failure Censoring. Austrian Journal of Statistics, 48(1), 14-37. https://doi.org/https://doi.org/10.17713/ajs.v47i4.638
Section
Special Issue on Lifetime Data Modelling (closed)