Overview
- Contains both theory and R code with step-by-step examples and figures
- Uses YUIMA package to implement the latest techniques available in the literature of inference and simulation for stochastic processes
- Shows how to create the description of very abstract models in the same way they are described in theoretical papers but with an extremely easy interface
Part of the book series: Use R! (USE R)
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Keywords
- Lévy processes
- R language
- YUIMA
- computational statistics
- simulation and inference for stochastic processes
- stochastic differential equations
- levy
- Malliavin calculus
- CRAN
- Brownian motion
- Wiener process
- CARMA
- COGARCH
- quasi maximum likelihood estimation
- adaptive Bayes estimation
- structural change point analysis
- hypotheses testing
- asynchronous covariance estimation
- lead-lag estimation
- LASSO model selection
Table of contents (7 chapters)
-
The Yuima Framework
Authors and Affiliations
About the authors
Stefano M. Iacus, PhD, is full professor of statistics in the Department of Economics, Management and Quantitative Methods at the University of Milan. He has been a member of the R Core Team (1999-2014) for the development of the R statistical environment and is now a member of the R Foundation. His research interests include inference for stochastic processes, simulation, computational statistics, causal inference, text mining, and sentiment analysis.
Nakahiro Yoshida, PhD, is full professor at the Graduate School of Mathematical Sciences, University of Tokyo. He is working in theoretical statistics, probability theory, computational statistics, and financial data analysis. He was awarded the Japan Statistical Society Award in 2009 and the Analysis Prize from the Mathematical Society of Japan in 2006.
Bibliographic Information
Book Title: Simulation and Inference for Stochastic Processes with YUIMA
Book Subtitle: A Comprehensive R Framework for SDEs and Other Stochastic Processes
Authors: Stefano M. Iacus, Nakahiro Yoshida
Series Title: Use R!
DOI: https://doi.org/10.1007/978-3-319-55569-0
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer International Publishing AG, part of Springer Nature 2018
Softcover ISBN: 978-3-319-55567-6Published: 12 June 2018
eBook ISBN: 978-3-319-55569-0Published: 01 June 2018
Series ISSN: 2197-5736
Series E-ISSN: 2197-5744
Edition Number: 1
Number of Pages: XIII, 268
Number of Illustrations: 51 b/w illustrations, 32 illustrations in colour
Topics: Statistics and Computing/Statistics Programs, Probability and Statistics in Computer Science, Probability Theory and Stochastic Processes