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A Multivariate Change-Point Model for Change in Mean Vector and/or Covariance Structure

Summary: [This abstract is based on the authors' abstract.] A multivariate-analysis tool is described that can detect change in the mean vector and/or covariance matrix in addition to the epoch of change in an independent sequence of multivariate observations. The multivariate change model is investigated using generalize likelihood-ratio statistics applied sequentially and adapted to repeated use, enabling the monitoring of short runs and unknown parameter processes while controlling their run behavior. Possible applications include short run processes, sequential dynamic control, ambulatory monitoring, disease monitoring, and syndromic surveillance.

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  • Topics: Statistical Process Control (SPC)
  • Keywords: Shift point, Likelihood methods, Short runs, Start up process(es)
  • Author: Zamba, K. D.; Hawkins, Douglas M.
  • Journal: Journal of Quality Technology