This volume examines the theory of fractional Brownian motion and other long-memory
processes. Interesting topics for PhD students and specialists in probability theory …

We derive rates of contraction of posterior distributions on nonparametric or semiparametric
models based on Gaussian processes. The rate of contraction is shown to depend on the …

Abstract Theory of random processes needs a kind of normal distribution. This is why
Gaussian vectors and Gaussian distributions in infinite-dimensional spaces come into play …

The author describes the current state of the art in the theory of invariant random fields. This
theory is based on several different areas of mathematics, including probability theory …

Stochastic Analysis of Mixed Fractional Gaussian Processes presents the main tools
necessary to characterize Gaussian processes. The book focuses on the particular case of …

Springer Cham Heidelberg New York Dordrecht London are believed to be true and
accurate at the date of publication. Neither the publisher nor the authors or the editors give a …

Vector Quantization is the name given to discretization methods based on nearest
neighbour search. It was developed in the 1950s, mostly in signal processing and …

We study and answer the question posed in the title. The answer is derived from some new
necessary and sufficient conditions for equivalence of Gaussian processes with stationary …

We derive a precise link between series expansions of Gaussian random vectors in a
Banach space and Parseval frames in their reproducing kernel Hilbert space. The results …

Using the white noise space framework, we construct and study a class of Gaussian
processes with stationary increments, which include as particular cases the Brownian and …