Liberal Arts and Sciences
Roycraft Lab
Led by Benjamin Roycraft · Statistics
What we study
The Roycraft Lab studies complex data structures and networks using topological methods and statistical models. They analyze high-dimensional data to uncover patterns and relationships.
What working here is like
- Computational
- No organisms (data only)
- Coding required
- Papers
- 3
Recent papers, explained
- Pseudolikelihood estimators for graphical models: existence and uniqueness
2025 · Biometrika
Studies when and why pseudolikelihood estimators work for graphical models, a key tool in high-dimensional data analysis.
- Bootstrapping persistent Betti numbers and other stabilizing statistics
2023 · The Annals of Statistics
Tests a bootstrap method to estimate topological features like persistent Betti numbers in complex data.
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- On approximation theorems for the Euler characteristic with applications to the bootstrap
2021 · Electronic Journal of Statistics
Proves how well the Euler characteristic approximates data shapes, helping improve bootstrap methods for topological analysis.
Plain-language summaries are AI-written and reviewed by us; check the paper for details.
How to reach out
Benjamin Roycraft hasn't set up this page yet. You can also look them up in the UF directory (search “Benjamin Roycraft”).