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- Publications
- Influence

Unbiased Recursive Partitioning: A Conditional Inference Framework

- T. Hothorn, K. Hornik, A. Zeileis
- Mathematics
- 1 September 2006

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

Regression Models for Count Data in R

- A. Zeileis, C. Kleiber, S. Jackman
- Computer Science
- 29 July 2008

The classical Poisson, geometric and negative binomial regression models for count data belong to the family of generalized linear models and are available at the core of the statistics toolbox in… Expand

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

- C. Strobl, A. Boulesteix, A. Zeileis, T. Hothorn
- Computer Science, Medicine
- BMC Bioinformatics
- 25 January 2007

BackgroundVariable importance measures for random forests have been receiving increased attention as a means of variable selection in many classification tasks in bioinformatics and related… Expand

Conditional variable importance for random forests

- C. Strobl, A. Boulesteix, T. Kneib, Thomas Augustin, A. Zeileis
- Medicine, Computer Science
- BMC Bioinformatics
- 11 July 2008

BackgroundRandom forests are becoming increasingly popular in many scientific fields because they can cope with "small n large p" problems, complex interactions and even highly correlated predictor… Expand

Beta Regression in R

- Francisco Cribari-Neto, A. Zeileis
- Mathematics
- 5 April 2010

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

Diagnostic Checking in Regression Relationships

- A. Zeileis, T. Hothorn
- Computer Science
- 2015

is still one of the most popular tools for data analysis despite (or due to) its simple structure. Although it is appropriate in many situations, there are many pitfalls that might affect the quality… Expand

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kernlab - An S4 Package for Kernel Methods in R

- Alexandros Karatzoglou, A. Smola, K. Hornik, A. Zeileis
- Computer Science
- 2 November 2004

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… Expand

Implementing a Class of Permutation Tests: The coin Package

- T. Hothorn, K. Hornik, M. A. V. D. Wiel, A. Zeileis
- Computer Science
- 13 November 2008

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… Expand

zoo: S3 Infrastructure for Regular and Irregular Time Series

- A. Zeileis, G. Grothendieck
- Computer Science, Mathematics
- 21 May 2005

zoo is an R package providing an S3 class with methods for indexed totally ordered observations, such as discrete irregular time series. Its key design goals are independence of a particular… Expand

Applied Econometrics with R

- C. Kleiber, A. Zeileis
- Computer Science
- 28 August 2008

This is the first book on applied econometrics using the R system for statistical computing and graphics. It presents hands-on examples for a wide range of econometric models, from classical linear… Expand