What is it about?
In this study, using maximum likelihood estimation, a considerably effective change-point model is proposed for the generalized variance control chart in which the required statistics are calculated with its distributional properties. The procedure, when used with generalized variance control charts, would be helpful for practitioners both controlling the multivariate process dispersion and detecting the time of the change in the variance-covariance matrix of a process. The procedure starts after the chart issues a signal. Several structural changes for the variance-covariance matrix are considered and the precision and the accuracy of the proposed method are discussed.
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Why is it important?
In this study, we consider the use of the change point estimator of the multivariate dispersion once the sample generalized variance,S-chart, in which the required statistics are calculated based on its distributional properties, issues a signal.
Perspectives
For different structural changes in the variance-covariance matrix and various sample sizes, it is indicated that our change point estimator is considerably effective in both accuracy and precision. It is shown that the estimator is, respectively, effective in estimating the time for the case when one of the standard deviation increases while the other decreases.
İpek Deveci Kocakoç
Dokuz Eylul Universitesi
Read the Original
This page is a summary of: Estimation of Change Point in Generalized Variance Control Chart, Communications in Statistics - Simulation and Computation, February 2011, Taylor & Francis,
DOI: 10.1080/03610918.2010.542844.
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