Statistical Inference and Optimum Life Testing Plans Under Type-II Hybrid Censoring Scheme

Tanmay Sen, Yogesh Mani Tripathi and Ritwik Bhattacharya ()
Additional contact information
Tanmay Sen: Indian Institute of Technology Patna
Yogesh Mani Tripathi: Indian Institute of Technology Patna
Ritwik Bhattacharya: Centro de Investigación en Matemáticas (CIMAT)

Annals of Data Science, 2018, vol. 5, issue 4, No 10, 679-708

Abstract: Abstract This article considers estimation of unknown parameters and prediction of future observations of a generalized exponential distribution based on Type-II hybrid censored data. Bayes point and HPD interval estimates of the unknown parameters are obtained under the assumption of independent gamma priors. Different classical and Bayesian point predictors and prediction intervals are obtained in two-sample situation against squared error loss function. The optimum censoring schemes are computed under various optimality criteria. Monte Carlo simulations are performed to compare different methods and two data sets are analyzed for illustrative purposes.

Keywords: Bayes estimates; EM algorithm; Generalized exponential distribution; MH algorithm; Prediction; Optimal censoring (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://link.springer.com/10.1007/s40745-018-0158-z Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:aodasc:v:5:y:2018:i:4:d:10.1007_s40745-018-0158-z

Ordering information: This journal article can be ordered from
https://www.springer ... gement/journal/40745

DOI: 10.1007/s40745-018-0158-z

Access Statistics for this article

Annals of Data Science is currently edited by Yong Shi

More articles in Annals of Data Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().