FOUNDATIONS AND RECENT DEVELOPMENTS
will take place on May 4-8, 2020, at Villa del Grumello, on the shores of the Lake of Como, Italy.
Anna Maria Paganoni, Politecnico di Milano, IT
RobustStatistics@ComoLakeSchool is focused on giving a perspective on the modern challenges of robust statistics, combining novel statistical techniques with open problems in different application fields.
Robust statistics is at the forefront of statistical research, and a central topic in multidisciplinary science where mathematical ideas are used to model and understand the real world.
It is almost inevitable, when analyzing big data, to have to cope with errors or outliers. An outlier is an observation (or subset of observations) that seems inconsistent with the rest of the data set. Robust Statistics aims at reducing the incorrect measurement risks generated by outliers.
While outliers are generally easy to identify in low dimensional datasets, when it comes to multivariate data, or even heterogeneous multivariate data, this task becomes very difficult and must be based on a solid foundation.
In some applied fields, often the so-called "outliers" are of paramount interest (fraud detection is an example). Sometimes, additionally, outliers might cluster in such a way that they become interesting for their own pattern, which can be properly disentangled from the bulk of the data with the aid of robust methods.
The aim of the course is three-fold:
The topics covered by the course include regression, multivariate analysis, transformations, unsupervised classification and functional analysis. The school is designed for postgraduate development for both researchers and professional data analysts.
In order to foster active interaction among students and instructors, the school is targeted for a class of at most 30 qualified and selected participants. Deadline for applications: March 4, 2020.
For more information, please email to firstname.lastname@example.org