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Watching steps of a grand tour implementation

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Bartkowiak and Szustalewicz, 1997 (B&Sz), have proposed an implementation of the grand tour algorithm designed specially to detect outliers in multivariate data. The algorithm work by performing a sequence of rotations and projections onto a specific 2D-plane (Π proj). This is equivalent to perform a series of rotations yielding transformed coordinates of the data: X(tr) = XA, with A being the rotation matrix, while X and X,sup>(tr) denote the data matrices before and after the rotation appropriately. A superimposed concentration ellipse indicates the outstanding points. We complement the paper of B&Sz by considering some details and variants of the implementation of the grand tour algorithm. In particular we watch the trajectories of the projected points. Our concern is the denseness of the watched projctions. We look at the trajectories of the projected point visible in the Π proj plane and the frequencies of thier appearing in various sectors of that plane. In the Appendix we present the derivation of the formula for the rotation matrix A employed in each step of the algorithm for obtaining the transformed data coordinates.
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  • Institute of Computer Science, University of Wrocław 51-151, Wrocław, Przesmyckiego 20, Poland
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bwmeta1.element.baztech-article-BWA1-0001-0094
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