Application of copulas to multivariate control charts

DOI10.1016/j.jspi.2013.05.005zbMath1278.62181OpenAlexW2051980198MaRDI QIDQ393636

Ghislain Verdier

Publication date: 23 January 2014

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

Full work available at URL: https://doi.org/10.1016/j.jspi.2013.05.005

zbMATH Keywords

density estimationlevel setsstatistical process controlcopulas modeling

Mathematics Subject Classification ID

Characterization and structure theory for multivariate probability distributions; copulas (62H05) Applications of statistics in engineering and industry; control charts (62P30)

Related Items (11)

Bivariate copula-based CUSUM charts for monitoring conditional nonlinear processes with first-order autocorrelation ⋮ Trade and currency options hedging model ⋮ Bivariate copulas on the Hotelling's T² control chart ⋮ A bivariate zero-inflated Poisson control chart: Comments and corrections on earlier results ⋮ The efficiency of constructed bivariate copulas for MEWMA and Hotelling’s T² control charts ⋮ Research on fault diagnosis of flexible material R2R manufacturing system based on quality control chart and SoV ⋮ Unnamed Item ⋮ Multivariate copulas on the MCUSUM control chart ⋮ Some robust approaches based on copula for monitoring bivariate processes and component-wise assessment ⋮ Unnamed Item ⋮ On soft computing with random fuzzy sets in econometrics and machine learning

Uses Software

• copula
• copula

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• A goodness-of-fit test for multivariate multiparameter copulas based on multiplier central limit theorems
• An introduction to copulas.
• Semiparametric multivariate density estimation for positive data using copulas
• The \(L_1\) convergence of kernel density estimates
• Multivariate plug-in bandwidth selection
• Parametric versus nonparametric tolerance regions in detection problems
• DDMA-charts: nonparametric multivariate moving average control charts based on data depth
• A Computable Plug-In Estimator of Minimum Volume Sets for Novelty Detection
• Control Charts for Multivariate Processes
• A semiparametric estimation procedure of dependence parameters in multivariate families of distributions
• Estimation of density level sets with a given probability content

This page was built for publication: Application of copulas to multivariate control charts