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- Friedrich Leisch
- 2002

Sweave combines typesetting with L TEX and data anlysis with S into integrated statistical documents. When run through R or Splus, all data analysis output (tables, graphs, . . . ) is created on theâ€¦ (More)

- David Meyer, Friedrich Leisch, Kurt Hornik
- Neurocomputing
- 2003

Support vector machines (SVMs) are rarely benchmarked against other classi1cation or regression methods. We compare a popular SVM implementation (libsvm) to 16 classi1cation methods and 9 regressionâ€¦ (More)

- Friedrich Leisch
- 2003

This article was originally published as Leisch (2004b) in the Journal of Statistical Software. FlexMix implements a general framework for fitting discrete mixtures of regression models in the Râ€¦ (More)

- Friedrich Leisch
- 2005

A methodological and computational framework for centroid-based partitioning cluster analysis using arbitrary distance or similarity measures is presented. The power of highlevel statisticalâ€¦ (More)

This introduction to the R package strucchange is a (slightly) modified version of Zeileis, Leisch, Hornik, and Kleiber (2002), which reviews tests for structural change in linear regression modelsâ€¦ (More)

This article is a (slightly) modified version of GrÃ¼n and Leisch (2008b), published in the Journal of Statistical Software. flexmix provides infrastructure for flexible fitting of finite mixtureâ€¦ (More)

Archetypal analysis has the aim to represent observations in a multivariate data set as convex combinations of extremal points. This approach was introduced by Cutler and Breiman (1994); they definedâ€¦ (More)

- Bettina GrÃ¼n, Friedrich Leisch
- Computational Statistics & Data Analysis
- 2007

R package flexmix provides flexible modelling of finite mixtures of regression models using the EM algorithm. Several new features of the software such as fixed and nested varying effects forâ€¦ (More)

The capabilities of the package exams for automatic generation of (statistical) exams in R are extended by adding support for learning management systems: As in earlier versions of the package examâ€¦ (More)

- Adrian Trapletti, Friedrich Leisch, Kurt Hornik
- Neural Computation
- 2000

We consider autoregressive neural network (AR-NN) processes driven by additive noise and demonstrate that the characteristic roots of the shortcutsthe standard conditions from linear time-seriesâ€¦ (More)