Abstract: Assumptions play a pivotal role in the selection and efficacy of statistical models, as unmet assumptions can lead to flawed conclusions and impact decision-making. In both traditional ...

Researchers have created a statistical method that may allow public health and infectious disease forecasters to better predict disease reemergence, especially for preventable childhood infections ...

This is a preview. Log in through your library . Abstract In this paper, we extend and analyze a Bayesian hierarchical spatiotemporal model for physical systems. A novelty is to model the discrepancy ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Google is expanding its AI model family while addressing some of the ...

Researchers have created and preliminarily tested what they believe may be one of the first models for predicting who has the highest probability of being resistant to COVID-19 in spite of exposure to ...

New research by a team that included a Johns Hopkins engineer promises to enable more accurate ice-flow predictions, helping scientists better forecast how melting glaciers will contribute to rising ...

Models are making headlines amidst the COVID-19 pandemic and no, they aren’t the kind you would find walking the catwalk. Statistical models are being deployed to determine exactly when things might ...