Skip to main content
SpringerLink
Log in
Book cover

Simulation and Inference for Stochastic Processes with YUIMA

A Comprehensive R Framework for SDEs and Other Stochastic Processes

  • Book
  • © 2018
Download book PDF
Download book EPUB

Overview

Authors:
  1. Stefano M. Iacus

    1. Department of Economics, Management and Quantitative Methods, University of Milan, Milan, Italy

    View author publications

    You can also search for this author in PubMed   Google Scholar

  2. Nakahiro Yoshida

    1. Graduate School of Mathematical Sciences, University of Tokyo, Tokyo, Japan

    View author publications

    You can also search for this author in PubMed   Google Scholar

  • Contains both theory and R code with step-by-step examples and figures
  • Uses YUIMA package to implement the latest techniques available in the literature of inference and simulation for stochastic processes
  • Shows how to create the description of very abstract models in the same way they are described in theoretical papers but with an extremely easy interface

Part of the book series: Use R! (USE R)

Buy print copy

Softcover Book USD 69.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Table of contents (7 chapters)

  1. Front Matter

    Pages i-xiii
    Download chapter PDF

  2. The Yuima Framework

    1. Front Matter

      Pages 1-1
      Download chapter PDF

    2. The YUIMA Package

      • Stefano M. Iacus, Nakahiro Yoshida
      Pages 3-65
      Download chapter PDF

  3. Models and Inference

    1. Front Matter

      Pages 67-67
      Download chapter PDF

    2. Diffusion Processes

      • Stefano M. Iacus, Nakahiro Yoshida
      Pages 69-136
      Download chapter PDF

    3. Compound Poisson Processes

      • Stefano M. Iacus, Nakahiro Yoshida
      Pages 137-154
      Download chapter PDF

    4. Stochastic Differential Equations Driven by Lévy Processes

      • Stefano M. Iacus, Nakahiro Yoshida
      Pages 155-202
      Download chapter PDF

    5. Stochastic Differential Equations Driven by the Fractional Brownian Motion

      • Stefano M. Iacus, Nakahiro Yoshida
      Pages 203-213
      Download chapter PDF

    6. CARMA Models

      • Stefano M. Iacus, Nakahiro Yoshida
      Pages 215-236
      Download chapter PDF

    7. COGARCH Models

      • Stefano M. Iacus, Nakahiro Yoshida
      Pages 237-256
      Download chapter PDF

  4. Back Matter

    Pages 257-268
    Download chapter PDF
Back to top

Keywords

About this book

The YUIMA package is the first comprehensive R framework based on S4 classes and methods which allows for the simulation of stochastic differential equations driven by Wiener process, Lévy processes or fractional Brownian motion, as well as CARMA, COGARCH, and Point processes. The package performs various central statistical analyses such as quasi maximum likelihood estimation, adaptive Bayes estimation, structural change point analysis, hypotheses testing, asynchronous covariance estimation, lead-lag estimation, LASSO model selection, and so on. YUIMA also supports stochastic numerical analysis by fast computation of the expected value of functionals of stochastic processes through automatic asymptotic expansion by means of the Malliavin calculus. All models can be multidimensional, multiparametric or non parametric.The book explains briefly the underlying theory for simulation and inference of several classes of stochastic processes and then presents both simulation experiments and applications to real data. Although these processes have been originally proposed in physics and more recently in finance, they are becoming popular also in biology due to the fact the time course experimental data are now available. The YUIMA package, available on CRAN, can be freely downloaded and this companion book will make the user able to start his or her analysis from the first page.

Authors and Affiliations

  • Department of Economics, Management and Quantitative Methods, University of Milan, Milan, Italy

    Stefano M. Iacus

  • Graduate School of Mathematical Sciences, University of Tokyo, Tokyo, Japan

    Nakahiro Yoshida

About the authors

Stefano M. Iacus, PhD, is full professor of statistics in the Department of Economics, Management and Quantitative Methods at the University of Milan. He has been a member of the R Core Team (1999-2014) for the development of the R statistical environment and is now a member of the R Foundation. His research interests include inference for stochastic processes, simulation, computational statistics, causal inference, text mining, and sentiment analysis.

Nakahiro Yoshida, PhD, is full professor at the Graduate School of Mathematical Sciences, University of Tokyo. He is working in theoretical statistics, probability theory, computational statistics, and financial data analysis. He was awarded the Japan Statistical Society Award in 2009 and the Analysis Prize from the Mathematical Society of Japan in 2006.

Bibliographic Information

Publish with us

Policies and ethics

Back to top

Search

Navigation