Inference for Diffusion Processes

With Applications in Life Sciences

  • Christiane Fuchs

Table of contents

  1. Front Matter
    Pages i-xix
  2. Christiane Fuchs
    Pages 1-5
  3. Stochastic Modelling

    1. Front Matter
      Pages 7-7
    2. Christiane Fuchs
      Pages 9-30
    3. Christiane Fuchs
      Pages 101-129
  4. Statistical Inference

    1. Front Matter
      Pages 131-131
  5. Applications

    1. Front Matter
      Pages 279-279
    2. Christiane Fuchs
      Pages 281-303
    3. Christiane Fuchs
      Pages 305-369
    4. Christiane Fuchs
      Pages 371-373
  6. Back Matter
    Pages 375-430

About this book

Introduction

Diffusion processes are a promising instrument for realistically modelling the time-continuous evolution of phenomena not only in the natural sciences but also in finance and economics. Their mathematical theory, however, is challenging, and hence diffusion modelling is often carried out incorrectly, and the according statistical inference is considered almost exclusively by theoreticians. This book explains both topics in an illustrative way which also addresses practitioners. It provides a complete overview of the current state of research and presents important, novel insights. The theory is demonstrated using real data applications.

Keywords

Bayesian inference diffusion approximations epidemic modelling fluorescence recovery after photobleaching (FRAP) stochastic differential equations (SDE)

Authors and affiliations

  • Christiane Fuchs
    • 1
  1. 1., Institute for Bioinformatics and SystemsHelmholtz Zentrum MünchenNeuherbergGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-642-25969-2
  • Copyright Information Springer-Verlag Berlin Heidelberg 2013
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-642-25968-5
  • Online ISBN 978-3-642-25969-2
  • About this book