and irrelevant regressors in our model and propose a variable selection procedure that we show to perform well for models …

computationally prohibits the essential variable selection needed to attain a model with desirable predictive power devoid of … overfitting. This paper aims at devising an algorithm that can carry the task of variable selection in the presence of a large … mixture, and wherein variable selection is applied following the enhancement of the Poisson assumption by means of controlling …

state-of-the-art methods for variable selection in the time series framework: the one covariate at a time multiple testing …

Logit Approximation (BLA) for Competing Risk Framework; Adaptive and Exhaustive Variable Selection (AEVS) for automatic …