Simulation and Inference for Stochastic Processes with YUIMA

Discover the groundbreaking work of Stefano M. Iacus in his book, Simulation and Inference for Stochastic Processes with YUIMA, published by Springer International Publishing AG in 2018. This essential guide spans 268 pages and serves as the first comprehensive resource utilizing the YUIMA package, a robust R framework based on S4 classes and methods.

This innovative text covers the simulation of stochastic differential equations influenced by Wiener processes, Lévy processes, and fractional Brownian motion. Additionally, it delves into advanced topics such as CARMA, COGARCH, and Point processes, making it an invaluable resource for researchers and practitioners in statistics and applied mathematics. Equip yourself with the tools needed to navigate stochastic processes with confidence and precision.

Enhance your understanding of complex stochastic models today with this insightful book, perfect for academics and data scientists alike!