50 shades of Bayesian testing of hypotheses
Résumé
Hypothesis testing and model choice are quintessential questions for statistical inference and while the Bayesian paradigm seems ideally suited for answering these questions, it faces difficulties of its own ranging from prior modelling to calibration, to numerical implementation. This chapter reviews these difficulties, from a subjective and personal perspective.