A Bayesian model for multi-feature contact matrices that uses tensor structures and contingency table theory to satisfy structural constraints and impute missing contact features, validated on simulations and US/German survey data.
Flood , Sarah S
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
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A method sharpens joint partial identification bounds on causal effects across settings by exploiting unobserved correlations in omitted variable biases.
citing papers explorer
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Bayesian Modeling and Prediction of Generalized Contact Matrices
A Bayesian model for multi-feature contact matrices that uses tensor structures and contingency table theory to satisfy structural constraints and impute missing contact features, validated on simulations and US/German survey data.
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Partial Identification of Causal Effects that Vary by Setting
A method sharpens joint partial identification bounds on causal effects across settings by exploiting unobserved correlations in omitted variable biases.