Calibrate Your Eyes to Recognize High-Dimensional Shapes from Their Low-Dimensional Projections

Dianne Cook
1997 Journal of Statistical Software  
This paper provides a suite of datasets from standard multivariate distributions and simple high-dimensional geomtric shapes that can be used to visually calibrate new users of grand tours. It contains animations of 1-D, 2-D, 3-D, 4-D and 5-D grand tours, links to starting XGobi or XLispStat on the calibration data sets, and C code for generating a grand tour. The purpose of the paper is two-fold: providing code for the grand tour that others could pick up and modify (it is not easy to code
more » ... ot easy to code this version which is why there are very few implementations currently available), and secondly, provide a variety of training datasets to help new users get a visual sense for high-dimensional data. 1-D (as a sequence
doi:10.18637/jss.v002.i06 fatcat:d47xc4g2ivaqvkzi6ug5urctba