Скачать или смотреть Types of Priors: Informative vs. Non-Informative

@genaiexp In Bayesian inference, priors can be categorized into two main types: informative and non-informative. Informative priors bring in specific knowledge or strong beliefs about a parameter based on previous studies or expert opinion. They are used when we have substantial prior knowledge about the parameter of interest. On the other hand, non-informative priors, or vague priors, are used when little is known about the parameter. They aim to exert minimal influence on the posterior distribution, letting the data speak for itself. The choice between informative and non-informative priors depends on the context of the analysis and the amount of pre-existing information available. Selecting the appropriate type of prior is crucial as it influences the robustness and credibility of the Bayesian model.