title: Robust neural network with applications to credit portfolio data analysis.
abstract: In this article, we study nonparametric conditional quantile estimation via neural network structure. We proposed an estimation method that combines quantile regression and neural network (robust neural network, RNN). It provides good smoothing performance in the presence of outliers and can be used to construct prediction bands. A Majorization-Minimization (MM) algorithm was developed for optimization. Monte Carlo simulation study is conducted to assess the performance of RNN. Comparison with other nonparametric regression methods (e.g., local linear regression and regression splines) in real data application demonstrate the advantage of the newly proposed procedure.
authors.affiliation: Department of Statistics, The Pennsylvania State University University Park, PA 16802, USA.
authors.forename: Yijia
authors.initials: Y
authors.lastname: Feng
authors.forename: Runze
authors.initials: R
authors.lastname: Li
authors.forename: Agus
authors.initials: A
authors.lastname: Sudjianto
authors.forename: Yiyun
authors.initials: Y
authors.lastname: Zhang