What is it about?
This study builds a control chart to monitor mean and variance of multivariate t-distributed data using a state space model and Bayes’ factors, applying a modified EWMA chart with ARMA(1,1) model on simulated data.
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Why is it important?
It offers a novel statistical tool for quality control in complex data structures, improving process monitoring where multivariate t distributions and unknown parameters occur, enhancing accuracy in industrial and research settings.
Perspectives
Future research may apply this method to real-world data, explore alternative Bayesian techniques, and extend to other multivariate distributions or dynamic control chart frameworks for better industrial process control.
Dr. Delshad Shaker Ismael Botani
Salahaddin University-Erbil
Read the Original
This page is a summary of: Construction of a Control Chart Using SSM for Multivariate t Distribution Data, Tikrit Journal of Pure Science, January 2023, Tikrit University,
DOI: 10.25130/tjps.v22i3.725.
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