Principal components are a well established tool in dimension reduction. The extension to principal curves allows for general smooth curves which pass through the middle of a p-dimensional data cloud. In this paper local principal curves are introduced, which are based on the localization of...

We describe a stochastic model based on a branching process for analyzing surveillance data of infectious diseases that allows to make forecasts of the future development of the epidemic. The model is based on a Poisson branching process with immigration with additional adjustment for possible...

Weighting is a largely used concept in many fields of statistics and has frequently cause controversies on its justification and profit. In this paper, we analyze a weighted version of the well-known local polynomial regression estimators, derive their asymptotic bias and variance, and find that...