The effect of serial correlation on the in-control average run length of cumulative score charts

DOI10.1016/0378-3758(95)00153-0zbMath0854.62093OpenAlexW2025595446MaRDI QIDQ1923402

Walter Böhm, Peter Hackl

Publication date: 19 January 1997

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

Full work available at URL: https://doi.org/10.1016/0378-3758(95)00153-0

zbMATH Keywords

CUSUMMarkov chainserial correlationprocess controlparametrizationsscoresrun length distributioncorrelated random walkShewhart chartfirst-order autoregressive processMonte Carlo estimatesin-control average run lengthasymptotic average run lengthcumulative score chart

Mathematics Subject Classification ID

Applications of statistics in engineering and industry; control charts (62P30) Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.) (60J20) Sequential statistical analysis (62L10)

Related Items (4)

On the average run lengths of quality control schemes using a Markov chain approach ⋮ Inference for post-change parameters after sequential CUSUM test under AR(1) model ⋮ Unnamed Item ⋮ On average run lengths of control charts for autocorrelated processes

Cites Work

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• A test for a change in a parameter occurring at an unknown point
• Tables for Computing Bivariate Normal Probabilities
• A Combined Shewhart-Cumulative Score Quality Control Chart
• Finite Continuous Time Markov Chains
• A Control Chart Based on Cumulative Scores
• Note on a Distribution-Free CUSUM Technique
• The Effect of Serial Correlation on the Performance of CUSUM Tests
• Variable Sampling Interval Combined Shewart-Cumulative Score Quality Control Procedure
• A Cumulative Score Control Scheme

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