This course is compulsory on the BSc in Actuarial Science and BSc in Financial Mathematics and Statistics. This course is available on the BSc in Data Science, BSc in Econometrics and Mathematical ...

Modern statistical methodologies are increasingly focused on addressing the challenges associated with high-dimensional data through advanced techniques for variable selection and model estimation.

Introduces exploratory data analysis, probability theory, statistical inference, and data modeling. Topics include discrete and continuous probability distributions, expectation, laws of large numbers ...

A general program that focuses on the analysis of quantities, magnitudes, forms, and their relationships, using symbolic logic and language. Includes instruction in algebra, calculus, functional ...

Epistemic decision theory integrates formal models of rational belief with the processes of decision‐making under uncertainty. It addresses how agents should revise their credences in light of new and ...

Definition: A model is a family of possible distributions for some random variable . (Our data set is , so will generally be a big vector or matrix or even more complicated object.) We will assume ...

It is shown that the fiducial distribution in a group model, or more generally a quasigroup model, determines the optimal equivariant frequentist inference procedures. The proof does not rely on ...

Andrew Barron, an expert on statistical information theory, probability limit theorems, and neural networks, has been appointed the Charles C. and Dorothea S. Dilley Professor of Statistics and Data ...