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Sufficient dimension reduction of high-dimensional data through regularized covariance estimation
Rothman, Adam J
(PI)
Cook, R. Dennis
(CoPI)
Statistics (Twin Cities)
Project
:
Research project
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Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.
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Mathematics
Sufficient Dimension Reduction
100%
Covariance Estimation
80%
High-dimensional Data
72%
Statistical method
67%
High-dimensional
34%
Prediction
33%
Sample Size
32%
Methodology
30%
Covariance matrix
25%
Predictive Modeling
23%
Remote Sensing
21%
Climate
19%
Data Reduction
19%
Predictive Model
19%
Spectroscopy
18%
Dimensionality Reduction
18%
Alternatives
17%
Dimensional Analysis
17%
Estimator
16%
Computational Algorithm
16%
Deficiency
15%
Dimensionality
14%
Asymptotic Analysis
13%
Predictors
12%
Higher Dimensions
12%
Estimate
12%
Efficient Algorithms
12%
Regression
10%
Performance
8%
Subset
7%
Standards
7%