Von Mises statistics for strongly dependent random variables

Bootstrap for dependent Hilbert space-valued random variables with application to von Mises statistics

Statistical methods for functional data are of interest for many applications. In this paper, we prove a central limit theorem for random variables taking their values in a Hilbert space. The random variables are assumed to be weakly dependent in the sense of near epoch dependence, where the underlying process fulfills some mixing conditions. As parametric inference in an infinite dimensional s...

Von Mises Type Statistics for Single Site Updated Local Interaction Random Elds Running Title: Von Mises Statistics for Random Elds

Random eld models in image analysis and spatial statistics usually have local interactions. They can be simulated by Markov chains which update a single site at a time. The updating rules typically condition on only a few neighboring sites. If we want to approximate the expectation of a bounded function, can we make better use of the simulations than through the empirical estimator? We describe...

Cramér-Von Mises Statistics for Discrete Distributions

The Cramér-von Mises family of goodness-of-fit statistics is a well-known group of statistics used to test fit to a continuous distribution. In this article we extend the family to provide tests for discrete distributions. The statistics examined are the analogues of those associated with the names of Cramér-von Mises, Watson and Anderson-Darling, called W , U and A respectively, and their comp...

Von Mises' Definition of Random Sequences Reconsidered

Strong Laws for Weighted Sums of Negative Dependent Random Variables

In this paper, we discuss strong laws for weighted sums of pairwise negatively dependent random variables. The results on i.i.d case of Soo Hak Sung [9] are generalized and extended.