basic element, i.e. variable importance measures, cannot be computed straightforward when there are missing values in the …

Variable importance measures for random forests have been receiving increased attention as a means of variable … genetic markers relevant for the prediction of a certain disease. We show that random forest variable importance measures are … categories. Simulation studies are presented illustrating that, when random forest variable importance measures are used with …

derive, for each of the input variables, the variable importance from the obtained fit. In this article we propose a new … approach which involves for each variable separately 1) defining variable importance as a real valued parameter, 2) deriving … nonparametric) model, and 3) develop a corresponding double robust locally efficient estimator of this variable importance, obtained …

Van der Laan (2005) proposed a targeted method used to construct variable importance measures coupled with respective …. This article applies the Van der Laan (2005) variable importance measures and corresponding inference to HIV-1 sequence … transcriptase codon positions on the HIV-1 strand are assessed to determine their respective variable importance, with respect to an …