hddplot (0.57-2)

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Use Known Groups in High-Dimensional Data to Derive Scores for Plots.

http://www.maths.anu.edu.au/~johnm
http://cran.r-project.org/web/packages/hddplot

Cross-validated linear discriminant calculations determine the optimum number of features. Test and training scores from successive cross-validation steps determine, via a principal components calculation, a low-dimensional global space onto which test scores are projected, in order to plot them. Further functions are included that serve didactic purposes.

Maintainer: John Maindonald
Author(s): John Maindonald

License: GPL (>= 2)

Uses: MASS, multtest, knitr
Reverse depends: Metabonomic

Released 5 months ago.


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