Published by the Foundation for Open Access Statistics
Editors-in-chief: Bettina Grün, Edzer Pebesma & Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
The YUIMA Project: A Computational Framework for Simulation and Inference of Stochastic Differential Equations | Brouste | Journal of Statistical Software
Authors: Alexandre Brouste, Masaaki Fukasawa, Hideitsu Hino, Stefano Iacus, Kengo Kamatani, Yuta Koike, Hiroki Masuda, Ryosuke Nomura, Teppei Ogihara, Yasutaka Shimuzu, Masayuki Uchida, Nakahiro Yoshida
Title: The YUIMA Project: A Computational Framework for Simulation and Inference of Stochastic Differential Equations
Abstract: The YUIMA Project is an open source and collaborative effort aimed at developing the R package yuima for simulation and inference of stochastic differential equations. In the yuima package stochastic differential equations can be of very abstract type, multidimensional, driven by Wiener process or fractional Brownian motion with general Hurst parameter, with or without jumps specified as Lévy noise. The yuima package is intended to offer the basic infrastructure on which complex models and inference procedures can be built on. This paper explains the design of the yuima package and provides some examples of applications.

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Paper: The YUIMA Project: A Computational Framework for Simulation and Inference of Stochastic Differential Equations     Download PDF (Downloads: 4488)
Supplements:
yuima_1.0.2.tar.gz: R source package Download (Downloads: 290; 160KB)
v57i04.R: R example code from the paper Download (Downloads: 344; 15KB)

DOI: 10.18637/jss.v057.i04

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.