… In this set of simulations, we focus on the MSE performance of quantile smoothing splines
with the smoothing parameter automatically tuned using GACV. We compare GACV and …

… parameters automatically, we could optimize a GACV-type criterion. However, this function …
of a new GACV-type criterion specifically adapted to QAMs: the Quantile GACV (QGACV), the …

… the quantile smoothing spline framework, and take the basis functions to be cubic B-splines. …
We have found, however, that GACV often severely overfits for extreme quantiles, ie τ near …

… or two covariates using robust and flexible quantile regression splines. Novel aspects of the
… coefficient and a reformulation of the quantile smoothing problem based on a weighted data …

… To obtain the smoothing parameter estimates proposed here we begin with the generalized
approximate cross validation (GACV) estimate proposed in Xiang and Wahba (1996), which …

… that a quantile estimator with the smoothing parameter … to the regression spline setting
and smoothing spline setting, … If we calculate GACV with new candidates, the behavior of the …

… ’); (b) the same P-spline smoother with λ selected by the SIC λ reported in (3.3), (‘psplines
+ sic’); (c) the quantile smoothing splines with a total variation penalty and λ selected again by …

… a fast automatic choice of the amount of smoothing. Compared to the COBS implementation
of quantile smoothing–as applied to the LIDAR data–… GACV for quantile smoothing splines …

… and GACV, two smoothing parameter criteria discussed in Section 2.3, in choosing smoothing
… Again we consider the representative lower 10%, 30% and 50% quantiles. To study the …

… To solve this problem, we propose a new Bayesian quantile smoothing spline (NBQSS),
which considers a random scale parameter. To begin with, we justify its objective prior options …