Quantile planes without crossing via nonlinear programming. (January 2018)

• Record Type: Journal Article
• Authors: Hutson, Alan D.
• Is Part Of: Computer methods and programs in biomedicine. Volume 153(2018)
• Page Start: 185
• Page End: 190
• Publication Date: 2018-01
• Subjects: Bootstrap -- Monotonicity -- Nonlinear constraints -- Computational statistics; Medicine -- Computer programs -- Periodicals; Biology -- Computer programs -- Periodicals; Computers -- Periodicals; Medicine -- Periodicals; Médecine -- Logiciels -- Périodiques; Biologie -- Logiciels -- Périodiques; Biology -- Computer programs; Medicine -- Computer programs; Periodicals; Electronic journals; 610.28
• DOI: 10.1016/j.cmpb.2017.10.019
• Languages: English
• ISSNs: 0169-2607

Abstract

Abstract: Background and objective: In this note we propose a nonlinear programming approach for simultaneous fitting of quantile regression models for two or more quantiles. The approach is straightforward, flexible and practical. We apply this approach to a dataset of lactic acid values from a screening dataset in childhood malaria. Methods: We carry out the fitting of simultaneous quantile regression models using a specific definition of a quantile as an expectation via nonlinear programming methods given certain monotonicity constraints. Results: We illustrate through simulations and examples that are new approach to simultaneous quantile regression is practical and feasible. The approach is supplemented by providing a bootstrap framework for confidence interval estimation. Conclusions: Our nonlinear programming approach towards solving the simultaneous quantile regression fitting is shown to be a practical approach that should appeal to statistical practitioners.