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See detailHDclassif: An R Package for Model-Based Clustering and Discriminant Analysis of High-Dimensional Data
Berge, Laurent UL; Bouveyron, Charles; Girard, Stéphane

in Journal of Statistical Software (2012), 46(6),

This paper presents the R package HDclassif which is devoted to the clustering and the discriminant analysis of high-dimensional data. The classification methods proposed in the package result from a new ... [more ▼]

This paper presents the R package HDclassif which is devoted to the clustering and the discriminant analysis of high-dimensional data. The classification methods proposed in the package result from a new parametrization of the Gaussian mixture model which combines the idea of dimension reduction and model constraints on the covariance matrices. The supervised classification method using this parametrization is called high dimensional discriminant analysis (HDDA). In a similar manner, the associated clustering method is called high dimensional data clustering (HDDC) and uses the expectation-maximization algorithm for inference. In order to correctly fit the data, both methods estimate the specific subspace and the intrinsic dimension of the groups. Due to the constraints on the covariance matrices, the number of parameters to estimate is significantly lower than other model-based methods and this allows the methods to be stable and efficient in high dimensions. Two introductory examples illustrated with R codes allow the user to discover the hdda and hddc functions. Experiments on simulated and real datasets also compare HDDC and HDDA with existing classification methods on high-dimensional datasets. HDclassif is a free software and distributed under the general public license, as part of the R software project. [less ▲]

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See detailVRMLGen: An R package for 3D Data Visualization on the Web
Glaab, Enrico UL; Garibaldi, Jonathan M.; Krasnogor, Natalio

in Journal of Statistical Software (2010), 36(8), 1-18

The 3-dimensional representation and inspection of complex data is a frequently used strategy in many data analysis domains. Existing data mining software often lacks functionality that would enable users ... [more ▼]

The 3-dimensional representation and inspection of complex data is a frequently used strategy in many data analysis domains. Existing data mining software often lacks functionality that would enable users to explore 3D data interactively, especially if one wishes to make dynamic graphical representations directly viewable on the web. In this paper we present vrmlgen, a software package for the statistical programming language R to create 3D data visualizations in web formats like the Virtual Reality Markup Language (VRML) and LiveGraphics3D. vrmlgen can be used to generate 3D charts and bar plots, scatter plots with density estimation contour surfaces, and visualizations of height maps, 3D object models and parametric functions. For greater flexibility, the user can also access low-level plotting methods through a unified interface and freely group different function calls together to create new higher-level plotting methods. Additionally, we present a web tool allowing users to visualize 3D data online and test some of vrmlgen's features without the need to install any software on their computer. [less ▲]

Detailed reference viewed: 142 (5 UL)