Por Anabel Forte Deltell (Dept. Estadistica e Investigación Operativa - Universitat de València).
No matter which subject you do think about or when you do so you will always find an attempt to understand which is the right theory driving a process. This is the base for model selection, a challenging problem deeply studied by Bayesians and non-Bayesian statisticians. Particularly challenging is the problem of variable selection, a model selection process where each model contains a subset of potential variables. From an Objective Bayesian point of view, and since the pioneering work of Jeffreys (1961), many solutions have been proposed to select from such a set of models. This talk intends to be a tour along those methodologies trying to answer the questions of Why? Where? and How? doing Objective Bayesian Variable selection.
