Bayesian structural time series for biomedical sensor data: A flexible modeling framework for evaluating interventions
Fig 2
Schematic and illustration of the Bayesian structural time series.
Latent parameters and hyperparameters are shown in blue, observations are shown in green, covariates in yellow (with a property of posterior inclusion probability), coefficients in orange, and predictions in purple. Predictions have an associated credible interval shown in light purple. An illustrative example shows weight over time, with various covariates, being modeled. Covariate posterior inclusion probability is given by the size of the circle. Assuming an intervention of increased diet, the model detects a strong impact on the post-intervention weight.