Abstract
The comparison of out-of-control performance of multivariate control chart methods on autoregressive processes requires a consistent method of generating a multivariate process shift. By applying the shift to the mean vector of the noise series, the covariance structure of the data may be maintained. We present a program for generating multivariate autoregressive data with a shift in the mean vector of the noise series. The program can be used to generate multivariate data from a first order vector autoregressive model with a shift in the mean vector of the noise series. The data can then be used to compare the shift detection properties of multivariate control chart methods.
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