Exact inference on multiple exponential populations under a joint type-II progressive censoring scheme
DOI10.1080/02331888.2019.1682583zbMath1434.62206OpenAlexW2986413589WikidataQ115551606 ScholiaQ115551606MaRDI QIDQ5205853
Shuvashree Mondal, Debasis Kundu
Publication date: 17 December 2019
Published in: Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/02331888.2019.1682583
maximum likelihood estimatorconjugate priorprogressive censoring schemebootstrap confidence intervaltype-II censoring scheme
Parametric tolerance and confidence regions (62F25) Point estimation (62F10) Censored data models (62N01) Bootstrap, jackknife and other resampling methods (62F40) Estimation in survival analysis and censored data (62N02)
Related Items (1)
Cites Work
- Unnamed Item
- Unnamed Item
- The art of progressive censoring. Applications to reliability and quality
- Stochastic monotonicity of the MLE of exponential mean under different censoring schemes
- Exact likelihood inference for two exponential populations under joint type-II censoring
- More efficient and less time-consuming censoring designs for life testing
- Progressive censoring methodology: an appraisal (with comments and rejoinder)
- Bayesian analysis of progressively censored competing risks data
- Conditional Maximum Likelihood and Interval Estimation for Two Weibull Populations under Joint Type-II Progressive Censoring
- Exact Likelihood Inference for Two Exponential Populations Under Joint Progressive Type-II Censoring
- Exact Likelihood Inference forkExponential Populations Under Joint Type-II Censoring
- Exact Likelihood Inference forkExponential Populations Under Joint Progressive Type-II Censoring
- Bayesian Analysis of Different Hybrid and Progressive Life Tests
- Testing Statistical Hypotheses
This page was built for publication: Exact inference on multiple exponential populations under a joint type-II progressive censoring scheme