Monitoring multivariate data with high missing rate by pooling univariate statistics

DOI10.1007/s42952-022-00182-4OpenAlexW4289860647MaRDI QIDQ2111961

Seonghun Cho, Johan Lim, Youngrae Kim

Publication date: 17 January 2023

Published in: Journal of the Korean Statistical Society (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s42952-022-00182-4

zbMATH Keywords

missing valuesmultivariate datacontrol chartpooled component testWelch's approximation

Mathematics Subject Classification ID

Statistics (62-XX)

Uses Software

• MICE

Cites Work

• Estimating high-dimensional covariance and precision matrices under general missing dependence
• Fixed support positive-definite modification of covariance matrix estimators via linear shrinkage
• A Multivariate Two-Sample Mean Test for Small Sample Size and Missing Data
• Control Procedures for Residuals Associated with Principal Component Analysis
• Phase II monitoring of changes in mean from high‐dimensional data
• The Effect of Methods for Handling Missing Values on the Performance of the MEWMA Control Chart
• High-dimensional data monitoring using support machines
• Principal component analysis-based control charts using support vector machines for multivariate non-normal distributions
• Multivariate Control Charts Based on Hybrid Novelty Scores
• Unnamed Item

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