3 papers
stat.ME2025
The -PCA Framework: A Unified and Efficiency-Preserving Approach with Robust Variants
Hung Hung, Zhi-Yu Jou, Su-Yun Huang +1
Principal component analysis (PCA) is a fundamental tool in multivariate statistics, yet its sensitivity to outliers and limitations in distributed environments restrict its effect…
stat.ME2025
Minimum Copula Divergence for Robust Estimation
Shinto Eguchi, Shogo Kato
This paper introduces a robust estimation framework based solely on the copula function. We begin by introducing a family of divergence measures tailored for copulas, including the…
q-bio.PE2024
Information Geometry for Maximum Diversity Distributions
Shinto Eguchi
In recent years, biodiversity measures have gained prominence as essential tools for ecological and environmental assessments, particularly in the context of increasingly complex a…