Estimation of Parameters of the GIE Distribution Under Progressive Type-I Censoring
- https://doi.org/10.2991/jsta.d.210510.001How to use a DOI?
- Generalized inverted exponential distribution, Progressive Type-I censoring scheme, Maximum likelihood estimation, Bayesian estimation, Markov chain Monte Carlo, Metropolis–Hasting algorithm
In this paper, we consider generalized inverted exponential distribution which is capable of modeling various shapes of failure rates and aging processes. Based on progressive Type-I censored data, we consider the problem of estimation of parameters under classical and Bayesian approaches. In this regard, we obtain maximum likelihood estimates and Bayes estimates under squared error loss function. We also compute a 95% asymptotic confidence interval, bootstrap confidence intervals and highest posterior density (HPD) credible interval estimates. Finally, we analyze a real data set and conduct a Monte Carlo simulation study to compare the performance of the various proposed estimators.
- © 2021 The Authors. Published by Atlantis Press B.V.
- Open Access
- This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - JOUR AU - Mahmoud R. Mahmoud AU - Hiba Z. Muhammed AU - Ahmed R. El-Saeed AU - Ashraf D. Abdellatif PY - 2021 DA - 2021/05/19 TI - Estimation of Parameters of the GIE Distribution Under Progressive Type-I Censoring JO - Journal of Statistical Theory and Applications SP - 380 EP - 394 VL - 20 IS - 2 SN - 2214-1766 UR - https://doi.org/10.2991/jsta.d.210510.001 DO - https://doi.org/10.2991/jsta.d.210510.001 ID - Mahmoud2021 ER -