About this book
- Contains both theory and code with step-by-step examples and figures
- Uses YUIMA package to implement the latest techniques available in the literature of inference 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
Stefano M. Iacus, PhD, is full professor of statistics 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 now 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 a 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.
- DOI https://doi.org/10.1007/978-3-319-55569-0
- Copyright Information Springer International Publishing AG, part of Springer Nature 2018
- Publisher Name Springer, Cham
- eBook Packages Mathematics and Statistics
- Print ISBN 978-3-319-55567-6
- Online ISBN 978-3-319-55569-0
- Series Print ISSN 2197-5736
- Series Online ISSN 2197-5744
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