The Meridian model health score gives a unified view of model integrity by combining six individual health checks into one metric ranging from 0 to 100. While individual diagnostics provide granular insights into specific model components, the model health score provides an aggregate measure on a model's health for causal inference. See Model health score to learn more.
| Metric check | Status | Recommended action |
|---|---|---|
| Convergence | The model has likely converged, as all parameters have R-hat values < 1.2. | |
| Baseline | The posterior probability that the baseline is negative is 0.00. We recommend visually inspecting the baseline time series in the Model Fit charts to confirm this. | |
| Bayesian p-value | The Bayesian posterior predictive p-value is 0.98. The observed total outcome is consistent with the model's posterior predictive distribution. | |
| Goodness of fit | R-squared = 0.7738, MAPE = 0.2557, and wMAPE = 0.1998. These goodness-of-fit metrics are intended for guidance and relative comparison. | |
| Prior-posterior shift |
5/5 channels passed
|
The model has successfully learned from the data. This is a positive sign that your data was informative. |