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Variable selection for high dimensional multivariate outcomes
Tamar Sofer, Lee Dicker, Xihong Lin
School of Arts and Sciences, Statistics
Research output
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Contribution to journal
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Article
›
peer-review
13
Scopus citations
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Dive into the research topics of 'Variable selection for high dimensional multivariate outcomes'. Together they form a unique fingerprint.
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Mathematics
Variable Selection
56%
High-dimensional
44%
Bayesian Information Criterion
28%
Regression Coefficient
22%
Model Selection
21%
Coordinate Descent
14%
Diabetes
14%
Penalized Regression
14%
Two-stage Procedure
14%
Oracle Property
14%
Descent Algorithm
13%
Gene Expression
13%
Penalized Likelihood
13%
Parameter Tuning
13%
Multivariate Regression
13%
Pathway
13%
Regularity Conditions
10%
Covariates
9%
Graphics
9%
Evaluate
8%
Regression
8%
Simulation Study
7%
Estimator
6%
Performance
6%
Arbitrary
5%
Business & Economics
Variable Selection
100%
Matrix
48%
Model Selection
33%
Bayesian Information Criterion
30%
Regression Coefficient
26%
Gene Expression
15%
Diabetes
13%
Multivariate Regression
12%
Finite Sample
11%
Covariates
11%
Regularity
11%
Pathway
10%
Simulation Study
10%
Estimator
8%
Performance
4%