Multivariate analyses such as principal component analysis were among the first statistical methods employed to extract information from genetic markers. From their early applications to current ...

Agglomerative-polythetic methods (commonly known as `similarity methods') of hierarchically classifying elements into sets can take a large number of different forms, according to: (a) the type of ...

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

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 ...

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 ...

This course is available on the MSc in Statistics, MSc in Statistics (Financial Statistics), MSc in Statistics (Financial Statistics) (Research) and MSc in Statistics (Research). This course is ...

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 Statistics, MSc in Data Science, MSc in Health Data Science, MSc in Marketing, MSc in Statistics, MSc in Statistics (Financial Statistics), MSc in ...