Estimation and testing for time-varying quantile single-index models with longitudinal data

Jianbo Li, Heng Lian, Xuejun Jiang and Xinyuan Song

Computational Statistics & Data Analysis, 2018, vol. 118, issue C, 66-83

Abstract: Regarding semiparametric quantile regression, the existing literature is largely focused on independent observations. A time-varying quantile single-index model suitable for complex data is proposed, in which the responses and covariates are longitudinal/functional, with measurements taken at discrete time points. A statistic for testing whether the time effect is significant is developed. The proposed methodology is illustrated using Monte Carlo simulation and empirical data analysis.

Keywords: Asymptotic normality; B-splines; Check loss minimization; Single-index models; Quantile regression (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:118:y:2018:i:c:p:66-83

DOI: 10.1016/j.csda.2017.08.011

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