An imputation-based approach for parameter estimation in the presence of ambiguous censoring with application in industrial supply chain

DOI10.1214/10-AOAS348zbMath1220.62123arXiv1101.1365OpenAlexW3100429665MaRDI QIDQ542963

Samiran Ghosh

Publication date: 20 June 2011

Published in: The Annals of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1101.1365

zbMATH Keywords

reliabilitymaximum likelihood estimationimputationproportional sampling

Mathematics Subject Classification ID

Censored data models (62N01) Applications of statistics in engineering and industry; control charts (62P30) Estimation in survival analysis and censored data (62N02) Reliability and life testing (62N05)

Related Items (3)

On analysis of incomplete field failure data ⋮ An imputation-based approach for parameter estimation in the presence of ambiguous censoring with application in industrial supply chain ⋮ Study of an imputation algorithm for the analysis of interval-censored data

Uses Software

• SPLIDA

Cites Work

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• An imputation-based approach for parameter estimation in the presence of ambiguous censoring with application in industrial supply chain
• Notes on maximum likelihood estimation for the three-parameter Burr XII distribution
• Survival analysis. Techniques for censored and truncated data.
• The generalized extreme value distribution
• Estimating the parameters of a truncated weibull distribution
• Maximum Likelihood Estimation for the Three Parameter Weibull Distribution Based on Censored Samples

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