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20072022
most citedMissForest - nonparametric missing value imputation for mixed-type data

6.4k citations

Showing 2011Show all

6 papers · 1 filter

math.PR2011★ 25 cited

New concentration inequalities for suprema of empirical processes

Johannes Lederer, Sara van de Geer

While effective concentration inequalities for suprema of empirical processes exist under boundedness or strict tail assumptions, no comparable results have been available under co…

stat.ME2011★ 80 cited

Stable Graphical Model Estimation with Random Forests for Discrete, Continuous, and Mixed Variables

Bernd Fellinghauer, Peter Bühlmann, Martin Ryffel +2

A conditional independence graph is a concise representation of pairwise conditional independence among many variables. Graphical Random Forests (GRaFo) are a novel method for esti…

math.ST2011★ 43 cited

Asymptotic optimality of the Westfall--Young permutation procedure for multiple testing under dependence

Nicolai Meinshausen, Marloes H. Maathuis, Peter Bühlmann

Test statistics are often strongly dependent in large-scale multiple testing applications. Most corrections for multiplicity are unduly conservative for correlated test statistics,…

stat.AP2011★ 6.4k cited

MissForest - nonparametric missing value imputation for mixed-type data

Daniel J. Stekhoven, Peter Bühlmann

Modern data acquisition based on high-throughput technology is often facing the problem of missing data. Algorithms commonly used in the analysis of such large-scale data often dep…

stat.ME2011★ 234 cited

Characterization and Greedy Learning of Interventional Markov Equivalence Classes of Directed Acyclic Graphs

Alain Hauser, Peter Bühlmann

The investigation of directed acyclic graphs (DAGs) encoding the same Markov property, that is the same conditional independence relations of multivariate observational distributio…

stat.AP2011★ 64 cited

A dynamic nonstationary spatio-temporal model for short term prediction of precipitation

Fabio Sigrist, Hans R. Künsch, Werner A. Stahel

Precipitation is a complex physical process that varies in space and time. Predictions and interpolations at unobserved times and/or locations help to solve important problems in m…