Dimension reduction in time series under the presence of conditional heteroscedasticity.
Murilo da SilvaT. N. SriramYuan KePublished in: Comput. Stat. Data Anal. (2023)
Keyphrases
- dimension reduction
- high dimensional
- feature extraction
- singular value decomposition
- high dimensional data
- low dimensional
- linear discriminant analysis
- principal component analysis
- data mining and machine learning
- random projections
- high dimensional problems
- feature selection
- high dimensionality
- variable selection
- manifold learning
- partial least squares
- unsupervised learning
- discriminative information
- high dimensional data analysis
- nonlinear manifold
- cluster analysis
- feature space
- preprocessing
- dimensionality reduction
- dimension reduction methods
- data sets
- sparse metric learning
- qr decomposition
- image data
- image processing
- learning algorithm