Bayes Estimation of Shift Point in Normal Sequence and Its Application to Statistical Process Control

DOI10.1080/03610920802254214zbMath1159.62354OpenAlexW1989792810MaRDI QIDQ3622070

J. B. Shah, M. N. Patel

Publication date: 23 April 2009

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610920802254214

zbMATH Keywords

simulationnormal distributionBayes estimatorMCMC algorithmloss functionsshift point

Mathematics Subject Classification ID

Bayesian inference (62F15) Applications of statistics in engineering and industry; control charts (62P30)

Cites Work

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• Strong rules for detecting the number of breaks in a time series
• Generalized ridge regression estimators under the LINEX loss function
• Bayesian Estimation of Change Point in Inverse Weibull Sequence
• Bayes Estimation of Shift Point in Geometric Sequence
• Bayesian Estimation and Prediction Using Asymmetric Loss Functions
• Some Bayesian Inferences for a Changing Linear Model
• Point estimation under asymmetric loss functions for left-truncated exponential samples
• Optimization design of control charts based on Taguchi's loss function and random process shifts
• Weighted-loss-function CUSUM chart for monitoring mean and variance of a production process

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