A linked Tucker tensor factorization enables a joint individualized hurdle-ordinal regression model that uncovers spatially heterogeneous effects of fluoride and diet on paired caries and fluorosis outcomes.
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Data thinning splits area-level observations to enable out-of-sample validation of Fay-Herriot models, with recommendations for thinning parameters that balance bias and variance for stable model comparison.
A Bayesian mixed Hawkes process with Weibull baseline intensity and random effects is developed to model seizure clustering and heterogeneity in focal epilepsy from the Human Epilepsy Project data.
Bayesian spatiotemporal model with spatial deformation yields substantial predictive gains for incomplete matrix-variate responses under anisotropic spatial dependence.
citing papers explorer
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Linked-Tucker Factorized Individualized Regression for Paired Multivariate Categorical Outcomes
A linked Tucker tensor factorization enables a joint individualized hurdle-ordinal regression model that uncovers spatially heterogeneous effects of fluoride and diet on paired caries and fluorosis outcomes.
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On Data Thinning for Model Validation in Small Area Estimation
Data thinning splits area-level observations to enable out-of-sample validation of Fay-Herriot models, with recommendations for thinning parameters that balance bias and variance for stable model comparison.
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A Mixed Self-Exciting Process to Model Epileptic Seizures
A Bayesian mixed Hawkes process with Weibull baseline intensity and random effects is developed to model seizure clustering and heterogeneity in focal epilepsy from the Human Epilepsy Project data.
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Spatial deformation in a Bayesian spatiotemporal model for incomplete matrix-variate responses
Bayesian spatiotemporal model with spatial deformation yields substantial predictive gains for incomplete matrix-variate responses under anisotropic spatial dependence.