Posterior Predictive Checks

Posterior Predictive Checks are a statistical method used to validate a model by comparing its predictions to actual observed data. After a model has been fitted to data and we have inferred its parameters, we generate new data based on these parameters. We then compare this generated data to the actual data to see if they match. If the model can accurately simulate real-world data patterns, it suggests the model is reliable. This process helps ensure that the model we use for predictions is both accurate and robust, ultimately improving its usefulness in real-world applications.