Control charts of mean and variance using copula Markov SPC and conditional distribution by copula

DOI10.1080/03610918.2018.1547404zbMath1490.62503OpenAlexW2909138707WikidataQ128508531 ScholiaQ128508531MaRDI QIDQ5083963

Jaiwook Baik, Mitch Reller, Jong-Min Kim

Publication date: 21 June 2022

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2018.1547404

zbMATH Keywords

copuladirectional dependencecopula Markov SPC

Mathematics Subject Classification ID

Applications of statistics in engineering and industry; control charts (62P30)

Related Items (5)

The optimized CUSUM and EWMA multi-charts for jointly detecting a range of mean and variance change ⋮ Unnamed Item ⋮ Model diagnostic procedures for copula-based Markov chain models for statistical process control ⋮ Estimation under copula-based Markov normal mixture models for serially correlated data ⋮ A copula-based Markov chain model for serially dependent event times with a dependent terminal event

Uses Software

• CDVine
• Copula.Markov

Cites Work

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• Estimation of copula-based semiparametric time series models
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• Directional dependence via Gaussian copula beta regression model with asymmetric GARCH marginals
• A model for association in bivariate life tables and its application in epidemiological studies of familial tendency in chronic disease incidence
• R routines for performing estimation and statistical process control under copula-based time series models
• CONTINUOUS INSPECTION SCHEMES

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