A sequential order statistics approach to step-stress testing

DOI10.1007/s10463-010-0309-2zbMath1237.62100OpenAlexW2112767862MaRDI QIDQ421426

Narayanaswamy Balakrishnan, Maria Kateri, Udo Kamps

Publication date: 23 May 2012

Published in: Annals of the Institute of Statistical Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10463-010-0309-2

zbMATH Keywords

maximum likelihood estimationorder restricted inferencegeneralized order statisticsk-out-of-n systemlocation-scale family of distributions

Mathematics Subject Classification ID

Order statistics; empirical distribution functions (62G30) Sequential statistical analysis (62L10) Reliability and life testing (62N05) Sequential estimation (62L12)

Related Items (14)

Inference in a model of successive failures with shape-adjusted hazard rates ⋮ Testing the validity of a link function assumption in repeated type-II censored general step-stress experiments ⋮ Stage life testing with random stage changing times ⋮ Distances between models of generalized order statistics ⋮ Classification using sequential order statistics ⋮ Hypotheses testing for generalized order statistics with simple order restrictions on model parameters under the alternative ⋮ Bayesian estimation and prediction with multiply type-II censored samples of sequential order statistics from one- and two-parameter exponential distributions ⋮ Confidence regions in step-stress experiments with multiple samples under repeated type-II censoring ⋮ Inference from multiple samples of Weibull sequential order statistics ⋮ Meta-analysis of general step-stress experiments under repeated type-II censoring ⋮ Sequential order statistics with an order statistics prior ⋮ Estimation in a Model of Sequential Order Statistics with Ordered Hazard Rates ⋮ Two-sample Bayesian prediction for sequential order statistics from exponential distribution based on multiply Type-II censored samples ⋮ General Model for Reliability-Based Engineering Design

Uses Software

• SPLIDA

Cites Work

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• Estimation with sequential order statistics from exponential distributions
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