Change Point Estimation of Multivariate Linear Profiles Under Linear Drift

Reza Baradaran Kazemzadeh · Rassoul Noorossana · Mona Ayoubi

21 citations0/0 files storedCommunications in Statistics - Simulation and Computation

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Advanced Statistical Process Monitoring Fault Detection and Control Systems Advanced Statistical Methods and Models

Abstract

In this paper, maximum likelihood estimators (MLE) for both step and linear drift changes in the regression parameters of multivariate linear profiles are developed. Performance of the proposed estimators is compared under linear drift changes in the regression parameters when a combined MEWMA and Chi-square control charts method signals an out-of-control condition. The effect of smoothing parameter of MEWMA control charts, missing data, and multiple drift changes on the performance of the both estimators is also evaluated. The application of the proposed estimators is also investigated thorough a numerical example resulted from a real case.

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References

2000On-Line Monitoring When the Process Yields a Linear Profile 2004Using Control Charts to Monitor Process and Product Quality Profiles 2003On the Monitoring of Linear Profiles 2004Phase I Analysis of Linear Profiles With Calibration Applications 2007Current research on profile monitoring 2007Monitoring General Linear Profiles Using Multivariate Exponentially Weighted Moving Average Schemes 2006A change point method for linear profile data 2006A control chart based on a change-point model for monitoring linear profiles

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2016A variance change point estimation method based on intelligent ensemble model for quality fluctuation analysis 2015Monotonic change point estimation of generalized linear model-based regression profiles 2019Simultaneous monitoring of mean vector and covariance matrix of multivariate simple linear profiles in the presence of within profile autocorrelation 2016An Area‐based Methodology for the Monitoring of General Linear Profiles

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