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 ...

The goal of this talk is to familiarize those in attendance with some common multivariate methods, such as principal component analysis, factor analysis, Hotelling’s T 2, etc. We’ll try to motivate ...

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 ...

In multivariate recurrent event data regression, observation of recurrent events is usually terminated by other events that are associated with the recurrent event processes, resulting in informative ...

Our research group develops modern and efficient multivariate statistical methods tailored for different types of multivariate data, such as time series, spatial data, spatio-temporal data, or ...

This course is available on the MPhil/PhD in Environmental Economics, MPhil/PhD in International Relations, MPhil/PhD in International Relations, MPhil/PhD in Social Policy, MPhil/PhD in Social ...

April 12, 2007 Robust statistical analysis methods capable of dealing with large complex data sets are required more than ever before in almost all branches of science. The European Science Foundation ...

This course is available on the Global MSc in Management, Global MSc in Management (CEMS MIM), Global MSc in Management (MBA Exchange), MSc in Applied Social Data Science, MSc in European and ...