Recursive binary partitioning is a popular tool for regression analysis. Two fundamental problems of exhaustive search procedures usually applied to fit such models have been known for a long time:… Expand

We identify two mechanisms responsible for this finding: (i) a preference for the selection of correlated predictors in the tree building process and (ii) an additional advantage for correlated predictor variables induced by the unconditional permutation scheme.Expand

We show that random forest variable importance measures are a sensible means for variable selection in many applications, but are not reliable in situations where potential predictor variables vary in their scale of measurement or their number of categories.Expand

The class of beta regression models is commonly used by practitioners to model variables that assume values in the standard unit interval (0, 1). It is based on the assumption that the dependent… Expand

We present applications of the tests contained in lmtest to two different data sets: the first is a macroeconomic time series from the U.S. analysed by Stock and Watson (1996) and the second is data from a study on measurments of fetal mandible length.Expand

kernlab is an extensible package for kernel-based machine learning methods in R. It takes advantage of R's new S4 ob ject model and provides a framework for creating and using kernel- based algorithms.Expand

The R package coin implements a unified approach to permutation tests providing a huge class of independence tests for nominal, ordered, numeric and censored data as well as multivariate data at mixed scales.Expand