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Estimation and testing for time-varying quantile single-index models with longitudinal data. (English) Zbl 1469.62102

Summary: 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.

MSC:

62-08 Computational methods for problems pertaining to statistics
62G08 Nonparametric regression and quantile regression

Software:

SemiPar; fda (R)
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Full Text: DOI

References:

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