Variable selection is a difficult problem in statistical model building. Identification of cost efficient diagnostic … factors is very important to health researchers, but most variable selection methods do not take into account the cost of … variable selection method to incorporate various costs of factors, where branch and bound search method is employed to …

neighbors and hence we may observe clusters of influence. We apply Bayesian Variable Selection (BVS) techniques and we use …

structure of the data-base, the sampling procedure and the influence of predictors. In particular we focus on the variable … selection problem, comparing innovative techniques based on shrinkage with traditional stepwise methods. The predictive …

selection operator (LASSO), this approach sets certain regression coefficients exactly to zero, thus performing variable … selection. However, such a framework, contrary to the LASSO, has never been used in regression models for survival data with …

neighbors and hence we may observe clusters of influence. We apply Bayesian Variable Selection (BVS) techniques and we use …