Quantile planes without crossing via nonlinear programming.

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.

authors

Hutson AD

doi

10.1016/j.cmpb.2017.10.019

subject

Has Abstract

pub_date

2018-01-01 00:00:00

pages

185-190

eissn

0169-2607

issn

1872-7565

pii

S0169-2607(17)30355-3

journal_volume

153

pub_type

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