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Tropical Statistics: New Frontiers in Max-Linear Data Analysis

Project description

Beyond Euclidean limits: building tropical statistical foundations

Traditional statistical methods often prove inadequate for data that resides in non-Euclidean environments, such as the complex geometric structures found in global economics and phylogenetics. Supported by the Marie Skłodowska-Curie Actions programme, the Tropical Statistics project aims to establish a rigorous statistical framework for tropical linear spaces –complex mathematical structures that better represent such data. The project will develop new methods to measure variation and create advanced mathematical models to analyse these unique environments. Key objectives include refining data analysis for faster interpretation and creating an accessible software package in R to help researchers apply these findings. By bridging this gap, Tropical Statistics will provide essential tools for phylogenetics and extreme value theory, enabling scientists to gain deeper insights where classical methods fail.

Objective

Classical statistics assumes data lies in a Euclidean space, but many problems involve non-Euclidean spaces such as manifolds or polyhedral complexes. Tropical linear spaces, which are polyhedral complexes defined by max-linear equations, are a promising but underdeveloped frontier for statistics. Such spaces capture data from a variety of domains, including phylogenetics, extreme-value theory and global economics, where classical methods fail. This proposal develops fundamental statistical measures such as variation, distributions, and models in the tropical setting.

The goal of this proposal is to advance our understanding of statistics in the tropical setting through the following four objectives. (O1) concerns the analysis of variation over tropical linear spaces using tropical principal components under the asymmetric tropical distance. Combining two previous approaches, asymmetric tropical PCA has the potential to offer fast, interpretable analysis of variation of max-linear data. (O2) outlines the next steps for fitting Gauss-Laplace distributions over tropical linear spaces, which is an important step in establishing the foundations of tropical statistics. (O3) defines a tropical probabilistic PCA model, which opens new avenues for statistical testing and Bayesian inference for max-linear data. (O4) implements these advancements in a software package in R, in order to facilitate the use of the results in applications.

Together, these advances lay the foundations for a rigorous statistical framework for tropical linear spaces. This will provide new insights and practical tools for researchers across phylogenetics, extreme-value theory, and global economics.

Fields of science (EuroSciVoc)

Programme(s)

Topic(s)

Funding Scheme

HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships

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Call for proposal

(opens in new window) HORIZON-MSCA-2025-PF

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Coordinator

UNIVERSIDAD POMPEU FABRA
Net EU contribution
€ 209 914,56
Address
PLACA DE LA MERCE, 10-12
08002 Barcelona
Spain
Region
Este Cataluña Barcelona
Activity type
Higher or Secondary Education Establishments
Links
Total cost
No data