 Conditional on a predictor being in the regression, we identify a prior distribution for the model coefficient, which corresponds to that variable ("β").A common choice on that step is to use a Normal prior with mean equal to zero and a large variance calculated based on formula_1 (where formula_2 is a design matrix of explanatory variables of the model).A draw of "γ" from its prior distribution is a list of the variables included in the regression.