Kernels are typically justified as a smoothing device in nonparametric analysis. We provide alternative interpretations which could lead to the use of asymmetric kernels. We thus derive the class of optimal asymmetric kernels, and analyse its main properties. We illustrate numerically its...

This paper deals with estimation and hypothesis testing in models allowing for trending processes that are possibly nonstationary, nonlinear, and non-Gaussian. Using semi-parametric estimators, we obtain asymptotic confidence intervals for the trend and memory parameters, and we develop joint...