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The Multivariate Statistical Engineering Group (MSERG) was set up in 2004 with the aim of providing the scientific community and the business world with a working environment in which to undertake research in the sphere of multivariate statistical techniques applied to improving the quality and productivity of processes. Several of the researchers in the group have lengthy experience in the discipline of multivariate statistical process control, (monitoring, fault detection & diagnosis, and predictive models), multivariate image analysis, and Six Sigma methodology for process improvement.

The GIEM group was formed by Professor Alberto Ferrer from his interest in the multivariate models, which led him to a research stay with Professor John F. MacGregor at McMaster University (Canada) in 1997. This research stay was a determining factor in Professor Ferrer’s vision, who starts talking about a new paradigm in Statistics to analyze MEGAVARIATE data structures.

Since then, the group  has developed its lines of research in various scientific fields that have experienced a breakthrough in the last decade: Multivariate Statistical Process Control (MSPC), Multivariate Image Analysis (MIA), “omic” sciences, N-way methods, Olfactory Sensometrics, or the recent Systems Biology.

Grupo de Ingeniería Estadística Multivariante · GIEM
Multivariate Statistical Engineering Research Group · MSERG