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Sparse sliced inverse regression for high dimensional data analysis
Haileab Hilafu,
Sandra E. Safo
Biostatistics
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peer-review
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Dive into the research topics of 'Sparse sliced inverse regression for high dimensional data analysis'. Together they form a unique fingerprint.
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Mathematics
Sliced Inverse Regression
100%
High-dimensional Data
80%
Data analysis
63%
Variable Selection
43%
Dimension Reduction
31%
Model
22%
Metabolomics
22%
Eigenvalue Decomposition
20%
Parsimony
19%
Generalized Eigenvalue
19%
Interpretability
18%
Selector
17%
Performance
16%
Sparsity
14%
Eigenvector
12%
Background
12%
Prediction
11%
Simulation Study
9%
Formulation
8%
Demonstrate
8%
Estimate
6%
Chemical Compounds
Dimension
52%
Reduction
31%
Decomposition
22%
Simulation
22%
Reaction Yield
14%
Application
11%
Medicine & Life Sciences
Data Analysis
52%
Metabolomics
15%
Engineering & Materials Science
Metabolomics
21%
Eigenvalues and eigenfunctions
14%
Decomposition
10%