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ARL Numerics for MEWMA Charts
by
Knoth, Sven
in
Accuracy
/ Approximation
/ Charts
/ Collocation
/ Computer programs
/ FORTRAN
/ Fredholm Integral Equation of the Second Kind
/ Markov Chain Approximation
/ Mathematical analysis
/ Multivariate Statistical Process Control
/ Nyström Method
/ Packages
/ Software
/ Software implementation
2017
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ARL Numerics for MEWMA Charts
by
Knoth, Sven
in
Accuracy
/ Approximation
/ Charts
/ Collocation
/ Computer programs
/ FORTRAN
/ Fredholm Integral Equation of the Second Kind
/ Markov Chain Approximation
/ Mathematical analysis
/ Multivariate Statistical Process Control
/ Nyström Method
/ Packages
/ Software
/ Software implementation
2017
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Do you wish to request the book?
ARL Numerics for MEWMA Charts
by
Knoth, Sven
in
Accuracy
/ Approximation
/ Charts
/ Collocation
/ Computer programs
/ FORTRAN
/ Fredholm Integral Equation of the Second Kind
/ Markov Chain Approximation
/ Mathematical analysis
/ Multivariate Statistical Process Control
/ Nyström Method
/ Packages
/ Software
/ Software implementation
2017
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Journal Article
ARL Numerics for MEWMA Charts
2017
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Overview
The FORTRAN code in Bodden and Rigdon (1999) for the in-control average run length (ARL) of multivariate exponentially weighted moving average charts (MEWMA) became quite popular and is widely used in statistical software systems such as MINITAB and STATISTICA. We find that the algorithms' accuracy is poor for low-dimensional processes. The Markov chain approximation described in Runger and Prabhu (1996) is not able to resolve the issue. The same holds for the calculation of the out-of-control ARL as proposed in Ridgon (1995b). We present two concepts that achieve higher accuracy for all dimensions. The competing numerical procedures are implemented in the R package spc.
Publisher
Taylor & Francis,Taylor & Francis Ltd
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