A new penalized geographically weighted compositional regression detects both contiguous and non-contiguous spatial clusters with shared effects when linking income distributions to COPD prevalence.
Polson and James G
4 Pith papers cite this work. Polarity classification is still indexing.
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A linked Tucker tensor factorization enables a joint individualized hurdle-ordinal regression model that uncovers spatially heterogeneous effects of fluoride and diet on paired caries and fluorosis outcomes.
For exchangeable hypotheses the optimal FWER-controlling multiple-testing procedure is computed via elementary symmetric polynomials on likelihood ratios plus a monotonicity theorem that enables an efficient bisection coordinate-descent algorithm.
A functional central limit theorem for pattern frequencies in 2D samples enables nonparametric goodness-of-fit, two-sample, and symmetry tests for copulas, with bootstrap critical values and parametric examples.
citing papers explorer
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Linking COPD Prevalence with Income Distribution: A Spatial Heterogeneous Compositional Regression via Geographically Weighted Penalized Approach
A new penalized geographically weighted compositional regression detects both contiguous and non-contiguous spatial clusters with shared effects when linking income distributions to COPD prevalence.
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Linked-Tucker Factorized Individualized Regression for Paired Multivariate Categorical Outcomes
A linked Tucker tensor factorization enables a joint individualized hurdle-ordinal regression model that uncovers spatially heterogeneous effects of fluoride and diet on paired caries and fluorosis outcomes.
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Optimal multiple testing under family-wise error control: elementary symmetric polynomials and a scalable algorithm
For exchangeable hypotheses the optimal FWER-controlling multiple-testing procedure is computed via elementary symmetric polynomials on likelihood ratios plus a monotonicity theorem that enables an efficient bisection coordinate-descent algorithm.
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Pattern-based tests for two-dimensional copulas
A functional central limit theorem for pattern frequencies in 2D samples enables nonparametric goodness-of-fit, two-sample, and symmetry tests for copulas, with bootstrap critical values and parametric examples.