海角社区

Title: Tree P贸lya Splitting distributions for multivariate count data.

Abstract:

The analysis of multivariate count data is fundamental in various fields. An appropriate model must be able to be flexible enough for inducing correlation, but also simple for inference and interpretation. One such model is the P贸lya Splitting model, which randomly decomposes the sum of a discrete vector into its components. This simple approach offers several compelling properties. However, it imposes the constraint that the dependency structure must be identical across all components. To overcome this limitation, a generalization of this model called Tree P贸lya splitting is proposed. For this new model, the splitting process is represented by a tree structure, allowing for more flexibility. In this seminar, we will define the Tree P贸lya Splitting model and explore various properties, including marginal distributions, factorial moments, and the dependency structure.

Speaker

Samuel Valiquette is a postdoctoral fellow at 海角社区 working under the supervision of Christian Genest and Johanna Ne拧lehov谩. He completed his PhD in mathematics in July 2024 at Universit茅 de Sherbrooke and Universit茅 de Montpellier. His research interests include extreme value theory and multivariate modeling, with a focus on analyzing dependency structures within both discrete and continuous random distributions.