Non-Gaussian Selfsimilar Stochastic Processes

Released on by Ciprian Tudor
preview-18

  • Non-Gaussian Selfsimilar Stochastic Processes Book Detail

  • Author : Ciprian Tudor
  • Release Date : 2023-07-04
  • Publisher : Springer Nature
  • Genre : Mathematics
  • Pages : 110
  • ISBN 13 : 3031337727
  • File Size : 38,38 MB
DOWNLOAD BOOK

Non-Gaussian Selfsimilar Stochastic Processes by Ciprian Tudor PDF Summary

Book Description: This book offers an introduction to the field of stochastic analysis of Hermite processes. These selfsimilar stochastic processes with stationary increments live in a Wiener chaos and include the fractional Brownian motion, the only Gaussian process in this class. Using the Wiener chaos theory and multiple stochastic integrals, the book covers the main properties of Hermite processes and their multiparameter counterparts, the Hermite sheets. It delves into the probability distribution of these stochastic processes and their sample paths, while also presenting the basics of stochastic integration theory with respect to Hermite processes and sheets. The book goes beyond theory and provides a thorough analysis of physical models driven by Hermite noise, including the Hermite Ornstein-Uhlenbeck process and the solution to the stochastic heat equation driven by such a random perturbation. Moreover, it explores up-to-date topics central to current research in statistical inference for Hermite-driven models.

Disclaimer: www.yourbookbest.com does not own Non-Gaussian Selfsimilar Stochastic Processes books pdf, neither created or scanned. We just provide the link that is already available on the internet, public domain and in Google Drive. If any way it violates the law or has any issues, then kindly mail us via contact us page to request the removal of the link.

Handbook of Probability

Handbook of Probability

File Size : 27,27 MB
Total View : 9211 Views
DOWNLOAD

THE COMPLETE COLLECTION NECESSARY FOR A CONCRETE UNDERSTANDING OF PROBABILITY Written in a clear, accessible, and comprehensive manner, the Handbook of Probabil