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Principal quantile regression for sufficient dimension reduction with heteroscedasticity
Chong Wang
,
Seung Jun Shin
, Yichao Wu
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peer-review
12
Citations (Scopus)
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Dive into the research topics of 'Principal quantile regression for sufficient dimension reduction with heteroscedasticity'. Together they form a unique fingerprint.
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Keyphrases
Heteroscedasticity
100%
Quantile Regression
100%
Sufficient Dimension Reduction
100%
Dimensionality Reduction
50%
Numerical Examples
25%
Statistical Methods
25%
Conditional Mean
25%
Model Assumptions
25%
Example-based
25%
Path Following
25%
Asymptotic Properties
25%
Solution Path
25%
Practice Data
25%
Kernel Trick
25%
Data Dimensionality
25%
Mathematics
Heteroscedasticity
100%
Quantile Regression
100%
Reduction Method
50%
Numerical Example
25%
Simulated Data
25%
Conditionals
25%
Statistical Method
25%
Real Data
25%
Asymptotic Property
25%
Economics, Econometrics and Finance
Statistical Method
100%