Stable Levy Processes Via Lamperti Type Representations


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Stable Lévy Processes via Lamperti-Type Representations


Stable Lévy Processes via Lamperti-Type Representations

Author: Andreas E. Kyprianou

language: en

Publisher: Cambridge University Press

Release Date: 2022-04-07


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A systematic treatment of stable Lévy processes and self-similar Markov processes, for graduate students and researchers in the field.

A Lifetime of Excursions Through Random Walks and Lévy Processes


A Lifetime of Excursions Through Random Walks and Lévy Processes

Author: Loïc Chaumont

language: en

Publisher: Springer Nature

Release Date: 2022-01-01


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This collection honours Ron Doney’s work and includes invited articles by his collaborators and friends. After an introduction reviewing Ron Doney’s mathematical achievements and how they have influenced the field, the contributed papers cover both discrete-time processes, including random walks and variants thereof, and continuous-time processes, including Lévy processes and diffusions. A good number of the articles are focused on classical fluctuation theory and its ramifications, the area for which Ron Doney is best known.

Brownian Motion And Potential Theory, Modern And Classical


Brownian Motion And Potential Theory, Modern And Classical

Author: Palle Jorgensen

language: en

Publisher: World Scientific

Release Date: 2024-10-29


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In this book, potential theory is presented in an inclusive and accessible manner, with the emphasis reaching from classical to modern, from analytic to probabilistic, and from Newtonian to abstract or axiomatic potential theory (including Dirichlet spaces). The reader is guided through stochastic analysis featuring Brownian motion in its early chapters to potential theory in its latter sections. This path covers the following themes: martingales, diffusion processes, semigroups and potential operators, analysis of super harmonic functions, Dirichlet problems, balayage, boundaries, and Green functions.The wide range of applications encompasses random walk models, especially reversible Markov processes, and statistical inference in machine learning models. However, the present volume considers the analysis from the point of view of function space theory, using Dirchlet energy as an inner product. This present volume is an expanded and revised version of an original set of lectures in the Aarhus University Mathematics Institute Lecture Note Series.