Most reinforcement learning methods for adaptive-traffic-signal-control require training from scratch to be applied on any new intersection or after any modi...

We consider the multivariate linear model for multilevel data where units are nested within a hierarchy of clusters. We propose permutation procedures to tes...

We consider the multivariate linear model for multilevel data where units are nested within a hierarchy of clusters. We propose permutation procedures to te...

We propose a method to build trees and forests when the response is a non-homogeneous Poisson process with excess zeros, based on two forests. The first one...

The log-rank test is commonly used as the split function in many commonly used survival trees and forests algorithms. However, the log-rank test may have a...

We consider the multivariate linear model for multilevel data where units are nested within a hierarchy of clusters. We propose permutation procedures to tes...

In this paper, we propose a multivariate random forest method for multiple responses of mixed types with missing responses. Imputation is performed for eac...

This paper presents a non--technical account of the developments in tree--based methods for the analysis of survival data with censoring. This review desc...

In this paper, we empirically investigate the robustness of random forests for regression problems. We also investigate the performance of five variations o...

This paper presents an extension of the well known random forest method to the case of clustered data. The proposed "mixed effects random forest" method is i...

This paper presents the generalized mixed effects regression tree (GMERT) method, an extension of the mixed effects regression tree (MERT) methodology design...

Discrete-time survival data with time-varying covariates are often encountered in practice. One such example is bankruptcy studies where the status of each f...

Tree based methods have not yet been adapted to handle mixed effects. Previous works extending them to accommodate correlated data are based on the multivari...

There has been a wide interest to extend univariate and multivariate nonparametric procedures to clustered and hierarchical data. Traditionally, parametric m...

This paper estimates a structural vector autoregression model to assess the dynamic effects of terrorism on output and prices in Israel over the post-1985 pe...

A weighted multivariate signed-rank test is introduced for an analysis of multivariate clustered data. Observations in different clusters may then get diffe...

In this paper, we propose a tree-based method for multivariate outcomes consisting in a mixture of categorical and continuous responses. The split function...

In this paper, we consider the nonparametric Behrens-Fisher problem with cluster correlated data. A class of weighted Mann-Whitney test statistics are intr...

Cet article dresse un portrait de l'état de la concurrence fiscale internationale par l'entremise i) de l'étude des taux d'impôt et autres caractéristiques...

This study examines simultaneously the effect of personal, contextual, and product-related factors on purchasing behaviour of fair-trade products. The resu...

Tree-based methods are frequently used in studies with censored survival time. Their structure and ease of interpretability make them useful to identify p...

In this paper, we consider the problem of constructing confidence intervals for a population median when the underlying population is discrete. We describe ...

In this paper, we consider testing the location parameter with multilevel (or hierarchical) data. A general family of weighted test statistics are introduced...

A weighted spatial median is proposed for the multivariate location problem with cluster correlated data. Its limiting distribution is derived under mild co...

Past studies have shown the unstability of unstructured peer-to-peer networks, in particular Gnutella. Because of this unstability, queries in these network...

Multivariate one-sample location problem for clustered data is considered from a nonparametric viewpoint. We develop the spatial median and its affine equiv...

We consider the multivariate location problem with cluster correlated data. A family of multivariate weighted sign tests are introduced for which observatio...

This paper presents and assesses a procedure to estimate conventional parameters characterizing fluctuations at the business cycle frequency, when the econ...

In this paper, we study the Pitman asymptotic efficiencies of the sign and the Wilcoxon signed-rank tests for cluster correlated data. A general expression ...

In this paper, we adapt the Wilcoxon signed-rank test to the case of cluster correlated data. A simple modification of the estimator of the asymptotic vari...

In this paper, we perform an empirical comparison of the classification error of several ensemble methods based on classification trees. This comparison is b...

We consider the problem of testing the hypothesis that a multivariate location vector is in the positive orthant. A conditionally distribution-free sign te...

A multivariate location model for cluster correlated observations is presented. An affine-invariant multivariate sign test for testing location is proposed...

The one-sided one sample problem with bivariate data is considered. A conditionally distribution-free sign test is proposed for that problem. This test is ...