The threshold vector error correction model is a popular tool for the analysis of spatial price transmission and market integration. In the literature, the profile likelihood estimator is the preferred choice for estimating this model. Yet, in certain settings this estimator performs poorly. In...

The threshold vector error correction model is a popular tool for the analysis of spatial price transmission. In the literature, the profile likelihood estimator is the preferred choice for estimating this model. Yet, in many settings this estimator performs poorly. In particular, if the true...

Conventional light microscopes have been used for centuries for the study of small length scales down to approximately 250 nm. Images from such a microscope are typically blurred and noisy, and the measurement error in such images can often be well approximated by Gaussian or Poisson noise. In...

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...

In this paper we describe some general methods for constructing goodness of fit tests in nonparametric regression models. Our main concern is the development of statisticial methodology for the assessment (validation) of specific parametric models M as they arise in various fields of...