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  • 标题:The YUIMA Project: A Computational Framework for Simulation and Inference of Stochastic Differential Equations
  • 本地全文:下载
  • 作者:Alexandre Brouste ; Masaaki Fukasawa ; Hideitsu Hino
  • 期刊名称:Journal of Statistical Software
  • 印刷版ISSN:1548-7660
  • 电子版ISSN:1548-7660
  • 出版年度:2014
  • 卷号:57
  • 期号:1
  • 页码:1-51
  • 语种:English
  • 出版社:University of California, Los Angeles
  • 摘要: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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