Nonparametric Estimation of a Conditional Quantile for α-Mixing Processes

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Local linear spatial quantile regression (2009, background): “For N = 1, [27] and [40] have studied the asymptotics of local polynomial fitting for quantile regression under general mixing conditions.”
Nonparametric Quantile Estimations for Dynamic Smooth Coefficient Models (2008, methodology): “Also, if there is no Xt in the model (d 1⁄4 0), qt(Ut, Xt) becomes qt(Ut) so that model (2) reduces to the ordinary nonparametric quantile regression model that has been studied extensively in the literature (e.g., Chaudhuri, Doksum and Samarov 1997; Yu and Jones 1998; Honda 2000; Cai 2002).”
Semiparametric quantile regression estimation in dynamic models with partially varying coefficients (2012, background): “KEY WORDS: Efficiency; nonlinear time series; partially linear; partially varying coefficients; quantile regression; semiparametric.”
Asymptotic Results of a Nonparametric Conditional Quantile Estimator for Functional Time Series (2008, background): “…when the data are i.i.d. or dependent and in finite dimensional spaces (see, for example, Bhattacharya and Gangopadhyay, 1990; Chaudhuri, 1991a,b; Fan et al., 1994; Honda, 2000; Jones and Hall, 1990; Mehra et al., 1991; Samanta, 1989; Welsh, 1996; Xiang, 1996, and the references therein).”