Variable selection in linear regression models: Choosing the best subset is not always the best choice
Variable selection in linear regression models: Choosing the best subset is not always the best choice
Abstract We consider the question of variable selection in linear regressions, in the sense of identifying the correct direct predictors (those variables that have nonzero coefficients given all candidate predictors). Best subset selection (BSS) is often considered the “gold standard,” with its use being restricted only by its NP‐hard nature. …