Heavy Tails and Long Range Dependence
Conference in honor of Gennady Samorodnitsky's 60th birthday.
Paris, June 20-22 2017
The workshop will focus on recent progress on theory and applications of ”non-standard” stochastic models, in particular those exhibiting heavy tails and/or long-range dependence. These models behave very differently from the ”usual” models that are typically based on Gaussian or Markovian stochastic processes. Both heavy tails and long-range dependence are observed in financial processes, teletraffic processes, climate/environmental data, and many other areas. Since many classical statistical tools break down in the presence of long-range dependence and/or absence of Gaussianity, it is important to understand how ”non-standard” models behave, how one simulates them, how one estimates their parameters, and how one predicts their behavior in the future. The workshop will include talks on self-similar (fractal-like) stochastic processes, stable and other infinitely divisible processes, geometry of the excursion sets of random fields, scale free random graphs, and connections between probability and ergodic theory.
Venue: Télécom Paris Tech, 46 rue Barrault, 75013 Paris
Registration (free but mandatory)
Scientific Committee Local organizing committee
Thomas Mikosch (chair)
Serge Cohen François Roueff
Vicky Fasen Philippe Soulier
Henrik Hult Maud Thomas
Bo Friis Nielsen Olivier Wintenberger
Cette conférence a bénéficié d’un financement public Investissement d’avenir, référence ANR-11-LABX-0056-LMH, LabEx LMH (programme math-STIC).