Simulation and Inference for Stochastic Processes with YUIMA: A Comprehensive R Framework for SDEs and Other Stochastic Processes

The YUIMA package is an R framework for simulating stochastic differential equations, performing central statistical analyses, and supporting stochastic numerical analysis. It is based on S4 classes and methods and can handle multidimensional, multiparametric, or non-parametric models. The book provides an overview of the theory and demonstrates applications in biology.

\n Format: Paperback / softback
\n Length: 268 pages
\n Publication date: 12 June 2018
\n Publisher: Springer International Publishing AG
\n

The YUIMA package stands as a groundbreaking R framework, built upon the powerful S4 classes and methods, enabling the simulation of diverse stochastic differential equations driven by Wiener processes, Lévy processes, or fractional Brownian motion. Moreover, it encompasses the simulation of CARMA, COGARCH, and Point processes. This comprehensive package offers a wide range of central statistical analyses, including quasi-maximum likelihood estimation, adaptive Bayes estimation, structural change point analysis, hypotheses testing, asynchronous covariance estimation, lead-lag estimation, LASSO model selection, and more. Furthermore, YUIMA excels in stochastic numerical analysis by efficiently computing the expected value of functionals of stochastic processes through automatic asymptotic expansion utilizing the Malliavin calculus. All models within YUIMA can be multidimensional, multiparametric, or non-parametric, catering to a wide array of applications.

In this companion book, we delve into the underlying theory behind the simulation and inference of various classes of stochastic processes. We then present both simulation experiments and practical applications to real-world data, showcasing the versatility and relevance of these processes across disciplines. While these processes were initially developed in physics and finance, their popularity is rapidly expanding into biology, fueled by the availability of time-course experimental data.

To facilitate your analysis journey, the YUIMA package is freely available on CRAN, allowing you to download and start your exploration from the very first page. Whether you are a researcher, data analyst, or practitioner, YUIMA empowers you to unlock the full potential of stochastic processes in your work.

\n Weight: 434g\n
Dimension: 160 x 238 x 19 (mm)\n
ISBN-13: 9783319555676\n
Edition number: 1st ed. 2018\n