4 papers
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…
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…
BaySC: Uncovering Tissue Architecture in Spatial Multi-Omics via Probabilistic Spatial Clustering
Xin Li, Xiaofei Dong, Zhenke Duan +5
Spatial domain identification requires jointly modeling molecular signatures and physical coordinates, yet current tools frequently over-smooth biological boundaries, require user-…
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…