Statistical Inference for Fractional Diffusion Processes

This book deals with Fractional Diffusion Processes and statistical inference for such stochastic processes. The main focus of the book is to consider parametric and nonparametric inference problems for fractional diffusion processes when a complete path of the process over a finite interval is observable.

Key features:

• Introduces self-similar processes, fractional Brownian motion and stochastic integration with respect to fractional Brownian motion.
• Provides a comprehensive review of statistical inference for processes driven by fractional Brownian motion for modelling long range dependence.
• Presents a study of parametric and nonparametric inference problems for the fractional diffusion process.
• Discusses the fractional Brownian sheet and infinite dimensional fractional Brownian motion.

• Includes recent results and developments in the area of statistical inference of fractional diffusion processes.

Researchers and students working on the statistics of fractional diffusion processes and applied mathematicians and statisticians involved in stochastic process modelling will benefit from this book.