Multivariate data analysis (MVDA) is being used to effectively handle complex datasets generated by process analytical technology (PAT) in biopharmaceutical process development and manufacturing.

In semiconductor manufacturing, especially in electrical test data, but also in other parameters, there are often sets of parameters that are very highly correlated. Even a change in the correlation ...

Multivariate testing, with its many combinations, creative needs, and more demanding implementation, is a great place for larger organizations to implement more rigorous processes. Testing helps build ...

Optimal design of sea-walls requires the extreme value analysis of a variety of oceanographic data. Asymptotic arguments suggest the use of multivariate extreme value models, but empirical studies ...

The Annals of Probability, Vol. 41, No. 2 (March 2013), pp. 1088-1114 (27 pages) The limit Gaussian distribution of multivariate weighted functionals of nonlinear transformations of Gaussian ...

Spatial point processes constitute a fundamental statistical framework for modelling the spatial distribution of events across a continuum. This field bridges theoretical developments in probability ...

TSD 20: Multivariate meta-analysis of summary data for combining treatment effects on correlated outcomes and evaluating surrogate endpoints (PDF, 1.2MB) – October 2019 – Updated December 2022: ...