Monitoring General Linear Profiles Using Multivariate Exponentially Weighted Moving Average Schemes
By Changliang Zou, Fugee Tsung, Zhaojun Wang. Technometrics, 2007
312 citations recorded by the source corpus.
Subfields: Control and Systems Engineering, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/5d978dbd12ffbf23bfeda5daf96843c7e899978c
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Control and Systems Engineering
- Yanfen Shang
- Changliang Zou
- Amirhossein Amiri
- Fugee Tsung
- Rassoul Noorossana
- Reza Baradaran Kazemzadeh
- Mehdi Koosha
- Armaghan Azhdari
In Statistics and Probability
- Amirhossein Amiri
- Changliang Zou
- Yanfen Shang
- Mehdi Koosha
- Armaghan Azhdari
- Guanghui Wang
- Fugee Tsung
- Reza Baradaran Kazemzadeh
Citations in the corpus
- Monitoring polynomial profiles in quality control applications (2009, methodology): “[19] proposed a multivariate EWMA (MEWMA) control chart for monitoring general linear profiles in phase II.”
- Phase I monitoring of generalized linear model-based regression profiles (2015, methodology): “[23] proposed an multivariate exponentially weighted moving average (MEWMA)based method for monitoring general linear profiles in Phase II.”
- Profile Monitoring with Binary Data and Random Predictors (2011, methodology): “Therefore, the setup of a scheme including one more chart is complicated and difficult (Zou et al. (2007a)).”
- A CUSUM-based method for monitoring simple linear profiles (2009, unknown): “[21] introduced practical applications of profiles.”
- Multivariate binomial/multinomial control chart (2014, background): “Therefore, Model (4) has certain links with the parametric profile monitoring, in which checking the stability of a linear or nonlinear regression model over time is of interest (Zou et al., 2007).”