A divide-and-conquer median posterior inference method scales Gaussian process regression for multi-pollutant mixture health effects, demonstrated on 650,000 birthweight records with negative associations for traffic pollutants.
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Scalable Gaussian Process Regression Via Median Posterior Inference for Estimating Multi-Pollutant Mixture Health Effects
A divide-and-conquer median posterior inference method scales Gaussian process regression for multi-pollutant mixture health effects, demonstrated on 650,000 birthweight records with negative associations for traffic pollutants.