Bayesfaktoreita
Bayesfaktoreita, often translated as Bayes factors, are a fundamental concept in Bayesian statistics used for model comparison. They quantify the evidence provided by the data in favor of one statistical model over another. A Bayes factor is essentially the ratio of the marginal likelihoods of the data under two competing models. The marginal likelihood integrates out the parameters of a model, providing a single number that represents how well the model predicts the observed data, averaged over all possible parameter values.
A Bayes factor greater than 1 indicates that the data provide more evidence for the numerator model
Bayes factors are particularly useful when comparing nested models (where one model is a special case of