The paper proposes a cross-validation method to address the question of specification search in a multiple nonlinear quantile regression framework. Linear parametric, spline-based partially linear and kernel-based fully nonparametric specifications are contrasted as competitors using...

In this paper we reconsider the results in Wang [Wang, J., 1995. Asymptotic normality of L1-estimators in nonlinear regression. J. Multivariate Anal. 54, 227-238; Wang, J., 1996. Asymptotics of least-squares estimators for constrained nonlinear regression. Ann. Statist. 4, 1316-1326], who studies...

This paper considers the implementation of prior stochastic information on unknown outcomes of the response variables into estimation and forecasting of systems of linear regression equations in the context of time series, cross sections, pooled and longitudinal data models. The established...

This paper studies the asymptotic behaviour of the unconditional quantile estimator for dependent random variables. Our proof is based on results from convex stochastic optimization and a mixing process which is specific to quantile estimation and requires only a small part of the...