A generally weighted moving average exceedance chart
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Date
Authors
Chakraborty, Niladri
Human, Schalk William
Balakrishnan, Narayanaswamy
Journal Title
Journal ISSN
Volume Title
Publisher
Taylor and Francis
Abstract
Distribution-free control charts gained momentum in recent years as they are more efficient in detecting a shift when there is a lack of information regarding the underlying process distribution. However, a distribution-free control chart for monitoring the process location often requires information on the in-control process median. This is somewhat challenging because, in practice, any information on the location parameter might not be known in advance and estimation of the parameter is therefore required. In view of this, a time-weighted control chart, labelled as the Generally Weighted Moving Average (GWMA) exceedance (EX) chart (in short GWMA-EX chart), is proposed for detection of a shift in the unknown process location; this chart is based on exceedance statistic when there is no information available on the process distribution. An extensive performance analysis shows that the proposed GWMA-EX control chart is, in many cases, better than its contenders.
Description
Keywords
Generally weighted moving average (GWMA), Nonparametric control chart, Monte Carlo simulation, Average run-length, Precedence statistic, Exceedance statistic, GWMA chart
Sustainable Development Goals
Citation
Niladri Chakraborty, Schalk W. Human & Narayanaswamy Balakrishnan (2018) A generally weighted moving average exceedance chart, Journal of Statistical Computation and Simulation, 88:9, 1759-1781, DOI: 10.1080/00949655.2018.1447573.
