A modular Bayesian model with predictive stacking estimates how a spatially and temporally misaligned exposure relates to a block-level health outcome, demonstrated on California ozone and asthma emergency visits.
A survey on star edge-coloring of graphs
1 Pith paper cite this work. Polarity classification is still indexing.
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abstract
The star chromatic index of a multigraph $G$, denoted $\chi'_{st}(G)$, is the minimum number of colors needed to properly color the edges of $G$ such that no path or cycle of length four is bicolored. We survey the results of determining the star chromatic index, present the interesting proofs and techniques, and collect many open problems and conjectures.
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Bayesian Inference for Spatially-Temporally Misaligned Data Using Predictive Stacking
A modular Bayesian model with predictive stacking estimates how a spatially and temporally misaligned exposure relates to a block-level health outcome, demonstrated on California ozone and asthma emergency visits.