Asymptotic and Bootstrap Tests for the Dimension of the Non-Gaussian Subspace.
Klaus NordhausenHannu OjaDavid E. TylerJoni VirtaPublished in: IEEE Signal Process. Lett. (2017)
Keyphrases
- high dimensional data
- confidence intervals
- hypothesis tests
- subspace clustering
- dimensionality reduction
- principal component analysis
- low dimensional
- worst case
- dimensional data
- model selection
- independent component analysis
- cross validation
- subspace learning
- high dimensional
- feature space
- heavy tailed
- multiple dimensions
- asymptotically optimal
- gaussian distribution
- principal components
- non stationary
- laplace transform
- machine learning
- clustering high dimensional data
- arbitrary dimension
- hypothesis testing
- sample size
- multi dimensional
- pattern recognition