A predictive Bayesian approach to EWMA and CUSUM charts for time-between-events monitoring
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Publication:5033456
DOI10.1080/00949655.2020.1793987OpenAlexW3042761863MaRDI QIDQ5033456
Publication date: 23 February 2022
Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/00949655.2020.1793987
Poisson processaverage run length (ARL)Bayesian CUSUMBayesian EWMABayesian process monitoringpredictive control limitsself-adaptive control chartssequential process monitoringtime-between-events control charts
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Cites Work
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- A predictive motivation for loss function specification in parametric hypothesis testing
- Combined Exponentially Weighted Moving Average Charts for the Mean and Variance Based on the Predictive Distribution
- Control Charts for the Variance and Coefficient of Variation Based on Their Predictive Distribution
- Multivariate Exponentially Weighted Moving Average Charts for a Mean Based on Its Prediction Distribution
- Control Charts for the Generalized Variance Based on Its Predictive Distribution
- Counted Data CUSUM's
- Markov Chains
- ON THE EVALUATION OF CONTROL CHART LIMITS BASED ON PREDICTIVE DISTRIBUTIONS
- Are estimated control charts in control?
- Monitoring poisson count data with probability control limits when sample sizes are time varying
- BayesianX̄control limits for exponentially distributed measurements
- A control chart for the Gamma distribution as a model of time between events
- CONTINUOUS INSPECTION SCHEMES