Recent research clearly shows that classic statistical approaches (e.g., those related to model parameter estimation) may be insufficient for describing phenomena observed in reality. There are many reasons for this, for example, the fact that in industrial data we observe impulsive behaviors, which indicate that the models describing the data are non-Gaussian, or in biological experiments (so-called single particle tracking), where we observe behaviors corresponding to models with random parameters. During this session, new statistical approaches and methods used to describe and analyze data with a complex structure will be presented. The theoretical results presented will be supported by real-world examples of data analysis from various fields.
Organized by:
Agnieszka Wyłomańska (Poland)Invited Speakers:
- Marek Arendarczyk (Poland)
- Michał Balcerek (Poland)
- Aleksandra Grzesiek (Poland)
- Joanna Janczura (Poland)
- Marcin Pitera (Poland)
- Wojciech Żuławiński (Poland)