Advancements in Symbolic Data Analysis
The sixth “One World webinar” organized by YoungStatS will take place on November 8th, 2021. With the development of digital systems, very large datasets have become routine. However, standard statistical approaches do not have the power or flexibility to analyse these efficiently, and extract the required knowledge. Symbolic Data Analysis provides a framework allowing for the representation of data with intrinsic variability, where the observed “values” are not just single real values or categories, but finite sets, intervals or distributions over a given domain. Methods for the (multivariate) analysis of such symbolic data have been developed, following different approaches, and using distinct criteria, which allow taking data variability into account.
Selected young researchers active in the area will present their recent contributions on this developing topic.
When & Where:
- Monday, November 8th, 12:00 Central European Time
- Online, via Zoom. The registration form is available here.
- Yuying Sun (Chinese Academy of Sciences, Beijing, China): “Model Averaging for Interval-valued Data”
- Boris Beranger (University of New South Wales, Australia): “Using symbolic data to understand underlying data behaviour”
- Bruno Pimentel (Universidade Federal de Alagoas, Brazil): “Kohonen Map-Wise Regression Applied to Interval Data”
- Sónia Dias (Polytechnic Institute of Viana do Castelo, Portugal): “Discriminant analysis of distributional data”
- Prof. Paula Brito, University of Porto, Portugal
The webinar is part of YoungStatS project of the Young Statisticians Europe initiative (FENStatS) supported by the Bernoulli Society for Mathematical Statistics and Probability and the Institute of Mathematical Statistics (IMS).
If you missed this webinar, you can watch the recording on our YouTube channel.