Informative priors revolutionize Bayesian inference, solving computational challenges and improving accuracy.
The article discusses how using informative priors in Bayesian inference can be beneficial. Informative priors help incorporate prior knowledge into models, which can improve computational efficiency and inference accuracy. The researchers provide three examples to show how informative priors can be used to address computational challenges and enhance the incorporation of external information into models.
