A generally weighted moving average exceedance chart. Issue 9 (13th June 2018)

• Record Type: Journal Article
• Authors: Chakraborty, Niladri; Human, Schalk W.; Balakrishnan, Narayanaswamy
• Is Part Of: Journal of statistical computation and simulation. Volume 88:Issue 9(2018)
• Page Start: 1759
• Page End: 1781
• Publication Date: 2018-06-13
• Subjects: Nonparametric control chart -- GWMA chart -- exceedance statistic -- precedence statistic -- average run-length -- Monte Carlo simulation; Mathematical statistics -- Data processing -- Periodicals; Digital computer simulation -- Periodicals; 519.5028505
• DOI: 10.1080/00949655.2018.1447573
• Languages: English
• ISSNs: 0094-9655

Abstract

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.