In many economic problems, we are often interested in the growth rate of a variable. Of particular importance is the situation where the rate of growth is constant or approximately constant. This often entails a model which assumes that a unit increase in the independent variable will be accompanied by a fixed proportional increase in the dependent variable, apart from random fluctuations. Unde...

Random forests are one of the most popular statistical learning algorithms, and a variety of methods for fitting random forests and related recursive partitioning approaches is available in R. This paper points out two important features of the random forest implementation cforest available in the party package: The resulting forests are unbiased and thus preferable to the randomForest implemen...

Variable selection has been suggested for Random Forests to improve their efficiency of data prediction and interpretation. However, its basic element, i.e. variable importance measures, can not be computed straightforward when there is missing data. Therefore an extensive simulation study has been conducted to explore possible solutions, i.e. multiple imputation, complete case analysis and a n...

MOTIVATION We developed an EM-random forest (EMRF) for Haseman-Elston quantitative trait linkage analysis that accounts for marker ambiguity and weighs each sib-pair according to the posterior identical by descent (IBD) distribution. The usual random forest (RF) variable importance (VI) index used to rank markers for variable selection is not optimal when applied to linkage data because of corr...

We define a new measure of variable importance of an exposure on a continuous outcome, accounting for potential confounders. The exposure features a reference level x(0) with positive mass and a continuum of other levels. For the purpose of estimating it, we fully develop the semi-parametric estimation methodology called targeted minimum loss estimation methodology (TMLE) [23, 22]. We cover the...

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Using multivariate design and modelling, the optimal conditions for electrodialytic remediation (EDR) of heavy metals were determined for polluted harbour sediments from Hammerfest harbour located in the geographic Arctic region of Norway. The comparative importance of the variables, current density, remediation time, light/no light, the liquid-solid ratio and stirring rate of the sediment susp...

We present a complete presentation of the theoretical results presented in the main text. We provide detailed analysis of the DStump algorithm in the context of a general additive regression model with uncorrelated design. We derive the results for the linear case as special case of the general theory. Our analysis is high-dimensional and non-asymptotic, and to our knowledge the first such anal...

In this paper, we study the selection of grouped variables using the random forests algorithm. We first propose a new importance measure adapted for groups of variables. Theoretical insights of this criterion are given for additive regression models. The second contribution of this paper is an original method for selecting functional variables based on the grouped variable importance measure. U...