Discover how multivariate models use multiple variables for investment forecasting, risk analysis, and decision-making in ...

Multivariate analysis is commonly used when we have more than one outcome variables for each observation. For instance, a survey of American adults’ physical and mental health might measure each ...

Professor Klaus Nordhausen develops modern multivariate statistical methods to analyze high-dimensional and large datasets in different fields.

Proceeding from the idea of Chernoff (1971, 1973) of representing multivariate data by faces, a new face is proposed in which the face parameters of the left and the right side can be varied ...

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

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: ...

Multivariate analysis in statistics is a set of useful methods for analyzing data when there are more than one variables under consideration. Multivariate analysis techniques may be used for several ...

Multivariate Analysis This course teaches methods to understand patterns and structures inherent in data sets containing many variables. The fundamentals of data visualisation, clustering, and ...