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Engineering and Technology
Austria
2026

D-Index & Metrics

Engineering and Technology

D-Index
64
Citations
46070
World Ranking
1588
National Ranking
6

Research.com Recognitions

  • 2026 - Research.com Engineering and Technology in Austria Leader Award
  • 2025 - Research.com Engineering and Technology in Austria Leader Award

Overview

Achim Zeileis is affiliated with the University of Innsbruck in Austria. Their research spans multiple fields, with a particular focus on environmental science and statistical methods.

The main fields of study covered by Achim Zeileis include:

  • Environmental Science

Within these fields, they have contributed to several subfields:

  • Global and Planetary Change
  • Statistics and Probability
  • Astronomy and Astrophysics
  • Atmospheric Science
  • Artificial Intelligence

The topics addressed by their work involve areas such as:

  • Fire effects on ecosystems
  • Lightning and Electromagnetic Phenomena
  • Statistical Methods and Inference
  • Meteorological Phenomena and Simulations
  • Statistical Methods and Bayesian Inference
  • Wind and Air Flow Studies
  • Climate variability and models

Achim Zeileis has collaborated frequently with several coauthors, including:

  • Georg J. Mayr
  • Thorsten Simon
  • Isabell Stucke
  • Deborah Morgenstern
  • Gerhard Diendorfer

They have published in various venues, notably:

  • arXiv (Cornell University)
  • Journal of Statistical Software
  • Weather and Climate Dynamics
  • Journal of the Royal Statistical Society Series C (Applied Statistics)
  • Nonlinear processes in geophysics

Selected recent publications by Achim Zeileis include:

  • Various Versatile Variances: An Object-Oriented Implementation of Clustered Covariances in R, 2020, Journal of Statistical Software
  • colorspace: A Toolbox for Manipulating and Assessing Colors and Palettes, 2020, Journal of Statistical Software

Other recent related works contributing to their research context include:

  • Remember the past: a comparison of time-adaptive training schemes for non-homogeneous regression, 2020, Nonlinear processes in geophysics
  • Network Trees: A Method for Recursively Partitioning Covariance Structures, 2020, Psychometrika
  • Predictive Distribution Modeling Using Transformation Forests, 2021, Journal of Computational and Graphical Statistics

Best Publications

  • Unbiased Recursive Partitioning: A Conditional Inference Framework

    Torsten Hothorn;Kurt Hornik;Achim Zeileis

  • Bias in random forest variable importance measures: Illustrations, sources and a solution

    Carolin Strobl;Anne-Laure Boulesteix;Achim Zeileis;Torsten Hothorn

  • Conditional variable importance for random forests

    Carolin Strobl;Anne Laure Boulesteix;Thomas Kneib;Thomas Augustin

  • Regression Models for Count Data in R

    Achim Zeileis;Christian Kleiber;Simon Jackman

  • Beta Regression in R

    Francisco Cribari-Neto;Achim Zeileis

  • kernlab - An S4 Package for Kernel Methods in R

    Alexandros Karatzoglou;Alexandros Smola;Kurt Hornik;Achim Zeileis

  • strucchange. An R package for testing for structural change in linear regression models.

    Achim Zeileis;Friedrich Leisch;Kurt Hornik;Christian Kleiber

  • Implementing a class of permutation pests: the coin package

    Torsten Hothorn;Kurt Hornik;Mark A. van de Wiel;Achim Zeileis

  • zoo: S3 Infrastructure for Regular and Irregular Time Series

    Achim Zeileis;Gabor Grothendieck

  • Econometric Computing with HC and HAC Covariance Matrix Estimators

    Achim Zeileis

  • Testing and dating of structural changes in practice

    Achim Zeileis;Christian Kleiber;Walter Krämer;Kurt Hornik

  • A Lego System for Conditional Inference

    Torsten Hothorn;Kurt Hornik;Mark A van de Wiel;Achim Zeileis

  • Model-Based Recursive Partitioning

    Achim Zeileis;Torsten Hothorn;Kurt Hornik

  • Partykit: a modular toolkit for recursive partytioning in R

    Torsten Hothorn;Achim Zeileis

  • Phenological change detection while accounting for abrupt and gradual trends in satellite image time series

    Jan Verbesselt;Robin Hyndman;Achim Zeileis;Darius Culvenor

  • Object-oriented Computation of Sandwich Estimators

    Achim Zeileis

  • Near real-time disturbance detection using satellite image time series

    Jan Verbesselt;Achim Zeileis;Martin Herold

  • Various Versatile Variances: An Object-Oriented Implementation of Clustered Covariances in R

    Achim Zeileis;Susanne Köll;Nathaniel Graham

  • Open-source machine learning: R meets Weka

    Kurt Hornik;Christian Buchta;Achim Zeileis

  • The Strucplot Framework: Visualizing Multi-way Contingency Tables with vcd

    David Meyer;Achim Zeileis;Kurt Hornik

Frequent Co-Authors

Kurt Hornik
Kurt Hornik Vienna University of Economics and Business
Friedrich Leisch
Friedrich Leisch BOKU University
Jan Verbesselt
Jan Verbesselt Wageningen University & Research
Thomas Kneib
Thomas Kneib University of Göttingen
Stefan Lang
Stefan Lang University of Innsbruck
Martin Herold
Martin Herold Wageningen University & Research
Roger Koenker
Roger Koenker University College London
Claus O. Wilke
Claus O. Wilke The University of Texas at Austin
Ting Wang
Ting Wang Washington University in St. Louis
Anne-Laure Boulesteix
Anne-Laure Boulesteix Ludwig-Maximilians-Universität München

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