Abstract The availability of many variables with predictive power makes their selection in a 2000 dodge durango catalytic converter regression context difficult.This study considers robust and understandable low-dimensional estimators as building blocks to improve overall predictive power by optimally combining these building blocks.Our new algorithm is based on generalized cross-validation and builds a predictive model step-by-step from a simple mean to more complex predictive combinations.
Empirical jeep grand cherokee 5.7 turbo kit applications to annual financial returns and actuarial telematics data show its usefulness in the financial and insurance industries.