We study nonparametric estimation of the volatility function of a diffusion process from discrete data, when the data are blurred by additional noise. This noise can be white or correlated, and serves as a model for microstructure effects in financial modeling, when the data are given on an...

We consider the problem of estimating the noise variance in homoscedastic nonparametric regression models. For low dimensional covariates "t"  is an element of  <openface>R</openface>-super-"d", "d"&equals;1, 2, difference-based estimators have been investigated in a series of papers. For a given length of such an...

Uniform confidence bands for densities "f" via non-parametric kernel estimates were first constructed by Bickel and Rosenblatt. In this paper this is extended to confidence bands in the deconvolution problem "g"&equals;"f"*"ψ" for an ordinary smooth error density "ψ". Under certain regularity...

Semiparametric models to describe the functional relationship between k groups of observations are broadly applied in statistical analysis, ranging from nonparametric ANOVA to proportional hazard (ph) rate models in survival analysis. In this paper we deal with the empirical assessment of the...

We present a new approach to handle dependencies within the general framework of case-control designs, illustrating our approach by a particular application from the field of genetic epidemiology. The method is derived for parent-offspring trios, which will later be relaxed to more general...