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Wang BH, Liang HY. Empirical likelihood in single-index quantile regression with high dimensional and missing observations. J Stat Plan Inference 2023. [DOI: 10.1016/j.jspi.2023.01.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
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Zu T, Lian H, Green B, Yu Y. Ultra-high Dimensional Quantile Regression for Longitudinal Data: an Application to Blood Pressure Analysis. J Am Stat Assoc 2022. [DOI: 10.1080/01621459.2022.2128806] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2022]
Affiliation(s)
- Tianhai Zu
- Department of Operations, Business Analytics, & Information Systems, University of Cincinnati, Cincinnati, Ohio, USA
| | - Heng Lian
- Department of Mathematics, City University of Hong Kong, Tat Chee Avenue, Kowloon Tong Hong Kong, China
| | - Brittany Green
- Department of Information Systems, Analytics, and Operations, University of Louisville, Louisville, Kentucky, USA
| | - Yan Yu
- Department of Operations, Business Analytics, & Information Systems, University of Cincinnati, Cincinnati, Ohio, USA
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