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http://hdl.handle.net/10397/106857
Title: | Linearized maximum rank correlation estimation | Authors: | Shen, G Chen, K Huang, J Lin, Y |
Issue Date: | Mar-2023 | Source: | Biometrika, Mar. 2023, v. 110, no. 1, p. 187-203 | Abstract: | We propose a linearized maximum rank correlation estimator for the single-index model. Unlike the existing maximum rank correlation and other rank-based methods, the proposed estimator has a closed-form expression, making it appealing in theory and computation. The proposed estimator is robust to outliers in the response and its construction does not need knowledge of the unknown link function or the error distribution. Under mild conditions, it is shown to be consistent and asymptotically normal when the predictors satisfy the linearity of the expectation assumption. A more general class of estimators is also studied. Inference procedures based on the plug-in rule or random weighting resampling are employed for variance estimation. The proposed method can be easily modified to accommodate censored data. It can also be extended to deal with high-dimensional data combined with a penalty function. Extensive simulation studies provide strong evidence that the proposed method works well in various practical situations. Its application is illustrated with the Beijing PM 2.5 dataset. | Keywords: | Censored data Closed-form solution Linearized maximum rank correlation Single-index model |
Publisher: | Oxford University Press | Journal: | Biometrika | ISSN: | 0006-3444 | EISSN: | 1464-3510 | DOI: | 10.1093/biomet/asac027 | Rights: | © The Author(s) 2022. Published by Oxford University Press on behalf of the Biometrika Trust. All rights reserved. This is a pre-copyedited, author-produced version of an article accepted for publication in Biometrika following peer review. The version of record Guohao Shen, Kani Chen, Jian Huang, Yuanyuan Lin, Linearized maximum rank correlation estimation, Biometrika, Volume 110, Issue 1, March 2023, Pages 187–203 is available online at: https://doi.org/10.1093/biomet/asac027. |
Appears in Collections: | Journal/Magazine Article |
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Shen_Linearized_Maximum_Rank_Main text.pdf | Pre-Published version | 365.87 kB | Adobe PDF | View/Open |
Shen_Linearized_Maximum_Rank_Supplement.pdf | Pre-Published version | 357.95 kB | Adobe PDF | View/Open |
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