Robust Modeling of Complex Systems with Heavy Tails and Long Memory

Abstract

We study non-standard, non-Gaussian stochastic models, emphasizing their large deviations, extreme values, statistical features and dependence properties with applications to several kinds of risk and complex systems. We focus on structural and distributional properties that explain critical relationships and promote realistic fitting of the models to data. Applications areas are complex networks including data networks, reliability estimation, risk analysis and financial control. The models are typically non-Gaussian, often driven by Poisson or Levy noises, may possess heavy tails and/or long range dependence and exhibit unusual fractal and scaling behavior.

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Document Details

Document Type
Technical Report
Publication Date
Jul 16, 2014
Accession Number
ADA613463

Entities

People

  • Gennady Samorodnitsky
  • Sidney Resnick

Organizations

  • Cornell University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Abstracts
  • Agreements
  • Complex Systems
  • Department Of Defense
  • Markov Chains
  • Markov Processes
  • Mathematics
  • Probability
  • Random Walk
  • Risk
  • Risk Analysis
  • Standards
  • Stationary Processes
  • Statistics
  • Stochastic Processes
  • Students
  • Theorems

Readers

  • Approximation Theory.
  • Theoretical Analysis.
  • Wave Propagation and Nonlinear Chaotic Dynamics.