Bandwidth Selection for Phylogenetic Tree Density Estimation
Research Paper#Phylogenetics, Density Estimation, Machine Learning🔬 Research|Analyzed: Jan 3, 2026 18:49•
Published: Dec 29, 2025 13:01
•1 min read
•ArXivAnalysis
This paper addresses the problem of bandwidth selection for kernel density estimation (KDE) applied to phylogenetic trees. It proposes a likelihood cross-validation (LCV) method for selecting the optimal bandwidth in a tropical KDE, a KDE variant using a specific distance metric for tree spaces. The paper's significance lies in providing a theoretically sound and computationally efficient method for density estimation on phylogenetic trees, which is crucial for analyzing evolutionary relationships. The use of LCV and the comparison with existing methods (nearest neighbors) are key contributions.
Key Takeaways
- •Proposes a likelihood cross-validation (LCV) method for bandwidth selection in tropical KDE.
- •Demonstrates improved performance (accuracy and computational time) of LCV compared to nearest neighbor methods.
- •Applies the method to both simulated and empirical (Apicomplexa genome) datasets.
Reference / Citation
View Original"The paper demonstrates that the LCV method provides a better-fit bandwidth parameter for tropical KDE, leading to improved accuracy and computational efficiency compared to nearest neighbor methods, as shown through simulations and empirical data analysis."