Robust Bayesian analysis

Robust Bayesian analysis is an approach within the Bayesian framework that aims to provide inference that is not overly sensitive to prior assumptions or model specifications. Traditional Bayesian analysis relies heavily on prior distributions and the chosen model, which can lead to results that are sensitive to the assumptions made. If the prior is misspecified or the model fails to capture the true underlying data-generating process, the conclusions drawn from the analysis can be misleading.