SUMMARY Semiparametric quantile regression is employed to flexibly estimate sales response for frequently purchased consumer goods. Using retail store‐level data, we compare the performance of models with and without monotonic smoothing for fit and prediction accuracy. We find that (a)...

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...

Splines constitute an interesting way to flexibly estimate a nonlinear relationship between several covariates and a response variable using linear regression techniques. The popularity of splines is due to their easy application and hence the low computational costs since their basis functions...

Splines are an attractive way of flexibly modeling a regression curve since their basis functions can be included like ordinary covariates in regression settings. An overview of least squares regression using splines is presented including many graphical illustrations and comprehensive examples....

Designing and pricing new products is one of the most critical activities for a firm, and it is well-known that taking into account consumer preferences for design decisions is essential for products later to be successful in a competitive environment (e.g., Urban and Hauser 1993). Consequently,...

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...