Gower distance-based multivariate control charts for a mixture of continuous and categorical variables
作者：
Highlights：
• We propose new nonparametric multivariate process monitoring techniques.
• Proposed control charts can efficiently handle mixed data.
• Integration of Gower’s dissimilarity coefficient and Hotelling’s T2 control charts.
• We examine the performance under various simulation and real scenarios.
• Performance of the method improves as the number of categorical variable increases.
摘要
Highlights•We propose new nonparametric multivariate process monitoring techniques.•Proposed control charts can efficiently handle mixed data.•Integration of Gower’s dissimilarity coefficient and Hotelling’s T2 control charts.•We examine the performance under various simulation and real scenarios.•Performance of the method improves as the number of categorical variable increases.
论文关键词：Gower distance,Multivariate control charts,Mixture data,Quality control,Statistical process control
论文评审过程：Available online 2 September 2013.
论文官网地址：https://doi.org/10.1016/j.eswa.2013.08.068
