In this paper uniform confidence bands are constructed for nonparametric quantile estimates of regression functions … respect to different education levels. -- Bootstrap ; Quantile Regression ; Confidence Bands ; Nonparametric Fitting ; Kernel …

This paper studies the performance of nonparametric quantile regression as a tool to predict Value at Risk (VaR). The ….1%) quantiles, where particularly few data points are available, we propose to combine nonparametric quantile regression with … specifications of the Conditionally Autoregressive VaR (CAViaR) models. -- Value at Risk ; nonparametric quantile regression ; risk …

A nonparametric procedure for quantile regression, or more generally nonparametric M-estimation, is proposed which is … completely data-driven and adapts locally to the regularity of the regression function. This is achieved by considering in each …. Simulations for different univariate median regression models show good finite sample properties, also in comparison to …

as well as quantile regression to weather risk indicators that are relevant from the viewpoint of agricultural production …

This article studies nonparametric estimation of a regression model for d ≥ 2 potentially non-stationary regressors. It … applicable nonparametric estimation technique before. Additive regression allows to circumvent the usual nonparametric curse of …

prior distributions such as a normal distribution or a Laplace distribituion for regression coefficients, which may be … suitable for median regression and exhibit no robustness to outliers. This paper develops a quantile regression on linear panel …

likelihood ratio test statistic for checking the stability of the regression coefficients. We derive both the exact and the …

We consider a varying coefficient regression model for sparse functional data, with time varying response variable …