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Simulation and Inference for Stochastic Processes with YUIMA

A Comprehensive R Framework for SDEs and Other Stochastic Processes

Authors: Iacus, Stefano M., Yoshida, Nakahiro

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  • 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
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イーブック ¥5,615
価格の適用国: Japan (日本円価格は個人のお客様のみ有効) (小計)
  • ISBN 978-3-319-55569-0
  • ウォーターマーク付、 DRMフリー
  • ファイル形式: EPUB, PDF
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  • ご購入後、すぐにダウンロードしていただけます。
ソフトカバー ¥7,019
価格の適用国: Japan (日本円価格は個人のお客様のみ有効) (小計)
  • ISBN 978-3-319-55567-6
  • 個人のお客様には、世界中どこでも配送料無料でお届けします。
  • Usually dispatched within 3 to 5 business days.
この書籍について

The YUIMA package is the first comprehensive R framework based on S4 classes and methods which allows for the simulation of stochastic differential equations driven by Wiener process, Lévy processes or fractional Brownian motion, as well as CARMA, COGARCH, and Point processes. The package performs various central statistical analyses such as quasi maximum likelihood estimation, adaptive Bayes estimation, structural change point analysis, hypotheses testing, asynchronous covariance estimation, lead-lag estimation, LASSO model selection, and so on. YUIMA also supports stochastic numerical analysis by fast computation of the expected value of functionals of stochastic processes through automatic asymptotic expansion by means of the Malliavin calculus. All models can be multidimensional, multiparametric or non parametric.The book explains briefly the underlying theory for simulation and inference of several classes of stochastic processes and then presents both simulation experiments and applications to real data. Although these processes have been originally proposed in physics and more recently in finance, they are becoming popular also in biology due to the fact the time course experimental data are now available. The YUIMA package, available on CRAN, can be freely downloaded and this companion book will make the user able to start his or her analysis from the first page.

著者について

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.

Table of contents (7 chapters)

Table of contents (7 chapters)

書籍の購入

イーブック ¥5,615
価格の適用国: Japan (日本円価格は個人のお客様のみ有効) (小計)
  • ISBN 978-3-319-55569-0
  • ウォーターマーク付、 DRMフリー
  • ファイル形式: EPUB, PDF
  • どの電子書籍リーダーからでもすぐにお読みいただけます。
  • ご購入後、すぐにダウンロードしていただけます。
ソフトカバー ¥7,019
価格の適用国: Japan (日本円価格は個人のお客様のみ有効) (小計)
  • ISBN 978-3-319-55567-6
  • 個人のお客様には、世界中どこでも配送料無料でお届けします。
  • Usually dispatched within 3 to 5 business days.
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書誌情報

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
Series Title
Use R!
Copyright
2018
Publisher
Springer International Publishing
Copyright Holder
Springer International Publishing AG, part of Springer Nature
イーブック ISBN
978-3-319-55569-0
DOI
10.1007/978-3-319-55569-0
ソフトカバー ISBN
978-3-319-55567-6
Series ISSN
2197-5736
Edition Number
1
Number of Pages
XIII, 268
Number of Illustrations
51 b/w illustrations, 32 illustrations in colour
Topics