ARC framework models high-dimensional compositional data with exact zeros by treating compositions as directions of latent vectors with an explicit active-set process on the hypersphere.
Journal of Applied Statistics , year = 2024, month = feb, volume =
4 Pith papers cite this work. Polarity classification is still indexing.
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Introduces tangential Bayes denoiser for Riemannian Gaussian mixtures on manifolds via spectral Laplace-Beltrami approximation, with nearly Bayes risk in low noise and minimax optimality on the circle.
A 4.5σ excess RM dispersion of 4.13 ± 0.91 rad m^{-2} is found in 191 Mg II sightlines versus controls, implying model-dependent CGM magnetic fields of 0.4-0.8 μG at projected radii 20-150 kpc and z~1.14.
Negative correlations between biomarkers maximize the combined AUC in multivariate normal models, with the largest gains when markers have equal predictive power, as shown by derivation, simulations, and pancreatic cancer metabolite data.
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Composition as Direction: An Active-Set Ray-Based Model for Sparse High-Dimensional Compositional Data
ARC framework models high-dimensional compositional data with exact zeros by treating compositions as directions of latent vectors with an explicit active-set process on the hypersphere.
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Evaluating the role of correlation among markers in prediction models
Negative correlations between biomarkers maximize the combined AUC in multivariate normal models, with the largest gains when markers have equal predictive power, as shown by derivation, simulations, and pancreatic cancer metabolite data.