Bayesian estimation and prediction with multiply type-II censored samples of sequential order statistics from one- and two-parameter exponential distributions

DOI10.1016/j.jspi.2010.11.009zbMath1204.62042OpenAlexW1987022811WikidataQ59180114 ScholiaQ59180114MaRDI QIDQ622459

N. Schenk, Erhard Cramer, Udo Kamps, Marco Burkschat

Publication date: 31 January 2011

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jspi.2010.11.009

zbMATH Keywords

order statisticsexponential distributionsBayesian estimationgeneralized order statisticssequential order statisticsmultiple samplesmultiply type-II censoring

Mathematics Subject Classification ID

Point estimation (62F10) Censored data models (62N01) Bayesian inference (62F15) Order statistics; empirical distribution functions (62G30) Sequential estimation (62L12)

Related Items

Bayesian prediction of future observations from weighted exponential distribution constant-stress model based on Type-II hybrid censored data ⋮ Progressively Type-II censored competing risks data for exponential distributions based on sequential order statistics ⋮ Some two-sample tests for simultaneously comparing both parameters of the shifted exponential models ⋮ Predicting observables from Weibull model based on general progressive censored data with asymmetric loss ⋮ Exact simultaneous location-scale tests for two shifted exponential samples ⋮ One-sample Bayesian prediction intervals based on progressively type-II censored data from the half-logistic distribution under progressive stress model ⋮ Estimates based on sequential order statistics with the two-parameter Pareto distribution ⋮ A dynamic system for Gompertz model ⋮ Two-sample Bayesian prediction for sequential order statistics from exponential distribution based on multiply Type-II censored samples ⋮ Optimal equivariant prediction regions based on multiply type-II censored generalized order statistics from exponential distributions ⋮ Type-I hybrid censoring of multiple samples

Uses Software

• SPLIDA

Cites Work

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