The areal modeling of the extremes of a natural process such as rainfall or temperature is
important in environmental statistics; for example, understanding extreme areal rainfall is …

Statistical issues arising in modelling univariate extremes of a random sample have been
successfully used in the most diverse fields, such as biometrics, finance, insurance and risk …

Dependence Modeling with Copulas covers the substantial advances that have taken place
in the field during the last 15 years, including vine copula modeling of high-dimensional …

This is a book about statistical distributions, their properties, and their application to
modelling the dependence of the location, scale, and shape of the distribution of a response …

We bring rigor to the vibrant activity of detecting power laws in empirical degree distributions
in real-world networks. We first provide a rigorous definition of power-law distributions …

Simultaneous sparse coding (SSC) or nonlocal image representation has shown great
potential in various low-level vision tasks, leading to several state-of-the-art image …

Long-memory, or more generally fractal, processes are known to play an important role in
many scientific disciplines and applied fields such as physics, geophysics, hydrology …

The aim of these Notes is to increase the reader's understanding of the spread of infectious
diseases using mathematics, and in particular stochastic methods. Needless to say …

Given a random sample x1, x2,..., xn from a population, we examine circumstances that lead
to some of the values being deemed outliers and the methodologies proposed to analyze …

Lévy processes form a wide and rich class of random process, and have many applications
ranging from physics to finance. Stochastic calculus is the mathematics of systems …