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stat.ME2026
Learning Collapsed Patterns in Compositional Data: A Bayesian Heterogeneous Relative-Shift Approach
Maoran Xu, Guanyu Hu
Relative-shift regression provides a principled framework for modeling compositional covariates by quantifying how the response changes when mass is reallocated from one component…
stat.ME2026
Linking COPD Prevalence with Income Distribution: A Spatial Heterogeneous Compositional Regression via Geographically Weighted Penalized Approach
Jingwen Deng, Shujie Ma, Sergio J. Rey +1
Income inequality is a major contributor to health disparities, yet its effects often vary by geography and are commonly represented as compositional distributions (e.g., proportio…
stat.ME2024★ 1 cited
Bayesian Spatially Clustered Compositional Regression: Linking intersectoral GDP contributions to Gini Coefficients
Jingcheng Meng, Yimeng Ren, Xuening Zhu +1
The Gini coefficient is an universally used measurement of income inequality. Intersectoral GDP contributions reveal the economic development of different sectors of the national e…