Projections of high-dimensional data onto low-dimensional subspaces provide insightful views for understanding multivariate relationships. This article discusses how to manually control the variable contributions to the projection. The user has control of the way a particular variable contributes to the viewed projection and can interactively adjust the variable's contribution. These manual controls complement the automatic views provided by a grand tour, or a guided tour, and give greatly improved flexibility to data analysts.
The purpose of the Journal of Computational and Graphical Statistics is to improve and extend the use of computational and graphical methods in statistics and data analysis. Established in 1992, this quarterly journal contains cutting-edge research, data, surveys, and more on numerical methods, graphical displays and methods, and perception. Articles are written for readers who have a strong background in statistics but are not necessarily experts in computing.
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Journal of Computational and Graphical Statistics
© 1997 American Statistical Association
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