We present a new multivariate technique for testing the significance of individual terms in a multifactorial analysis-of-variance model for multispecies response variables. The technique will allow researchers to base analyses on measures of association (distance measures) that are ecologically relevant. In addition, unlike other distance-based hypothesis-testing techniques, this method allows ...

Current high dimensional data visualization tools are not effective in helping users gain insights of the data for many domains and tasks. This paper presents HDDVis, a very accessible High Dimensional Data Visualization tool that allows user to interactively explore the datasets from both low-dimensional projections and parallel coordinates. The dimensionality reduction methods used by HDDVis ...

Mixtures of Probabilistic Principal Component Analyzers can be used to model data that lies on or near a low dimensional manifold in a high dimensional observation space, in effect tiling the manifold with local linear (Gaussian) patches. In order to exploit the low dimensional structure of the data manifold, the patches need to be localized and oriented in a low dimensional space, so that 'loc...

Comparing different methods of estimating the genetic diversity could define their usefulness in plant breeding programs. In this study, a total of 18 morphological traits and 20 simple sequence repeat (SSR) loci were used to study the morphological and genetic diversity among 20 maize hybrids selected from different countries, and to classify the hybrids into groups based on molecular profiles...

We address in this paper the problem of self-calibration and metric reconstruction (up to a scale) from one unknown motion of an uncalibrated stereo rig. The epipolar constraint is first formulated for two uncalibrated images. The problem then becomes one of estimating unknowns such that the discrepancy from the epipolar constraint, in terms of sum of squared distances between points and their ...

Principal components analysis is a well-known statistical method in dealing with large dependent data sets. It is also used in functional data for both purposes of data reduction as well as variation representation. On the other hand "handwriting" is one of the objects, studied in various statistical fields like pattern recognition and shape analysis. Considering time as the argument,...

2 Kac coordinates 5 2.1 Based automorphisms and affine root systems . . . . . . . . . . . . . . . . . . . . . . 6 2.2 Torsion points, Kac coordinates and the normalization algorithm . . . . . . . . . . . . 9 2.3 μm-actions on Lie algebras . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 2.4 Principal μm-actions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...