Inference for Diffusion Processes: With Applications in Life Sciences 2013th Edition

From the reviews:

“The book under review is aimed at introducing both modelling and inference for diffusions and applying the statistical estimation of complex diffusion models to real data sets. It addresses to theoreticians (e.g., mathematicians and statisticians) as well as practitioners (e.g., bioinformaticians and biologists) with basic knowledge about deterministic differential equations, probability theory and statistics. … the book under review is recommended to researchers with strong background through deterministic differential equations, probability theory and statistics.” (Iris Burkholder, zbMATH, Vol. 1276, 2014)

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.