We obtain uniform consistency results for kernel-weighted sample covariances in a nonstationary multiple regression framework that allows for both fixed design and random design coefficient variation. In the fixed design case these nonparametric sample covariances have different uniform...

In this paper, we study the local polynomial composite quantile regression (CQR) smoothing method for the nonlinear and nonparametric models under the Harris recurrent Markov chain framework. The local polynomial CQR regression method is a robust alternative to the widely-used local polynomial...

In this paper, we investigate the nonlinear quantile regression with mixed discrete and continuous regressors. A local linear smoothing technique with the mixed continuous and discrete kernel function is proposed to estimate the conditional quantile regression function. Under some mild...