From 2 November 2020, the autumn semester 2020 will take place online. Exceptions: Courses that can only be carried out with on-site presence.
Please note the information provided by the lecturers via e-mail. 401-3611-00L
Advanced Topics in Computational Statistics
Semester Autumn Semester 2016 Lecturers M. H. Maathuis Periodicity two-yearly recurring course Course Does not take place this semester. Language of instruction English
Abstract This lecture covers selected advanced topics in computational statistics, including various classification methods, the EM algorithm, clustering, handling missing data, and graphical modelling. Objective Students learn the theoretical foundations of the selected methods, as well as practical skills to apply these methods and to interpret their outcomes. Content The course is roughly divided in three parts: (1) Supervised learning via (variations of) nearest neighbor methods, (2) the EM algorithm and clustering, (3) handling missing data and graphical models. Lecture notes Lecture notes. Prerequisites / Notice We assume a solid background in mathematics, an introductory lecture in probability and statistics, and at least one more advanced course in statistics.