Skip to main navigation
Skip to search
Skip to main content
Experts@Minnesota Home
Home
Profiles
Research units
University Assets
Projects and Grants
Research output
Press/Media
Datasets
Activities
Fellowships, Honors, and Prizes
Search by expertise, name or affiliation
High-dimensional generalizations of asymmetric least squares regression and their applications
Yuwen Gu,
Hui Zou
Statistics (Twin Cities)
Research output
:
Contribution to journal
›
Article
›
peer-review
42
Scopus citations
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'High-dimensional generalizations of asymmetric least squares regression and their applications'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Mathematics
Least Squares Regression
100%
High-dimensional
67%
Least Squares
55%
Generalization
41%
Heteroscedasticity
16%
Quantile Regression
15%
Penalty
12%
Lasso
8%
High-dimensional Data
7%
Subset
7%
Econometrics
7%
Penalty Function
7%
Finance
7%
Overlap
7%
Higher Dimensions
6%
Efficient Algorithms
5%
Statistics
4%
Demonstrate
4%
Performance
4%
Business & Economics
Least Squares
89%
Quantile Regression
25%
Heteroscedasticity
16%
Penalty
12%
Penalty Function
9%
Finance
6%
Econometrics
5%
Statistics
5%
Performance
2%