Showing 1 - 6 of 6
through one-step penalized least squares estimation with the Kullback-Leibler divergence as the penalty function. Asymptotic …
Persistent link: https://www.econbiz.de/10010462645
In this paper uniform confidence bands are constructed for nonparametric quantile estimates of regression functions. The method is based on the bootstrap, where resampling is done from a suitably estimated empirical density function (edf) for residuals. It is known that the approximation error...
Persistent link: https://www.econbiz.de/10010270724
-step penalized least squares estimation with the Kullback-Leibler divergence as the penalty function. Asymptotic results of the …
Persistent link: https://www.econbiz.de/10010491441
through one-step penalized least squares estimation with the Kullback-Leibler divergence as the penalty function. Asymptotic …
Persistent link: https://www.econbiz.de/10011115466
Let (X1, Y1), . . ., (Xn, Yn) be i.i.d. rvs and let l(x) be the unknown p-quantile regression curve of Y on X. A quantile-smoother ln(x) is a localised, nonlinear estimator of l(x). The strong uniform consistency rate is established under general conditions. In many applications it is necessary...
Persistent link: https://www.econbiz.de/10005678022
In this paper uniform confidence bands are constructed for nonparametric quantile estimates of regression functions. The method is based on the bootstrap, where resampling is done from a suitably estimated empirical density function (edf) for residuals. It is known that the approximation error...
Persistent link: https://www.econbiz.de/10008476279