Ever since its introduction, the bootstrap has provided both a powerful set of solutions for
practical statisticians, and a rich source of theoretical and methodological problems for …

This survey intends to collect the developments on Goodness-of-Fit for regression models
during the last 20 years, from the very first origins with the proposals based on the idea of …

The majority of empirical research in economics ignores the potential benefits of
nonparametric methods, while the majority of advances in nonparametric theory ignores the …

This book contains a up-to-date overview of nonlinear time series models and their
application to modelling economic relationships. It considers nonlinear models in stationary …

This book provides an accessible collection of techniques for analyzing nonparametric and
semiparametric regression models. Worked examples include estimation of Engel curves …

This review is a primer for those who wish to familiarize themselves with nonparametric
econometrics. Though the underlying theory for many of these methods can be daunting for …

In the past two decades a parametric multivariate regression modelling approach for
analyzing growth curve data has achieved prominence. The approach, which has several …

We propose a nonparametric test of conditional independence based on the weighted
Hellinger distance between the two conditional densities, f (y| x, z) and f (y| x), which is …

Y is conditionally independent of Z given X if Pr {f (y| X, Z)= f (y| X)}= 1 for all y on its support,
wheref (·|·) denotes the conditional density of Y given (X, Z) or X. This paper proposes a …

In this paper we propose a test for the significance of categorical predictors in nonparametric
regression models. The test is fully data-driven and employs cross-validated smoothing …