This paper is concerned with the nonparametric estimation of regression quantiles where the response variable is … component functions in additive quantile regression models. …

We consider a class of nonparametric time series regression models in which the regressor takes values in a sequence … precise rate depending on the smoothness of the regression function and the dependence of the data in a non-trivial way. …

In this paper, we propose three new predictive models: the multi-step nonparametric predictive regression model and the … multi-step additive predictive regression model, in which the predictive variables are locally stationary time series; and … the multi-step time-varying coefficient predictive regression model, in which the predictive variables are stochastically …

We study a longitudinal data model with nonparametric regression functions that may vary across the observed subjects …. In a wide range of applications, it is natural to assume that not every subject has a completely different regression … the same regression curve. We develop a bandwidth-free clustering method to estimate the unknown group structure from the …