Geometric representation of high dimension, low sample size data
High dimension, low sample size data are emerging in various areas of science. We find a common structure underlying many such data sets by using a non-standard type of asymptotics: the dimension tends to ∞ while the sample size is fixed. Our analysis s
|Collections||ANU Research Publications|
|Source:||Journal of the Royal Statistical Society Series B|
|01_Hall_Geometric_representation_of_2005.pdf||244.41 kB||Adobe PDF||Request a copy|
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