The YUIMA Project is an open source academic project aimed at developing a complete environment for estimation and simulation of Stochastic Differential Equations and other Stochastic Processes via the R package called yuima and its Graphical User Interface yuimaGUI
120.000+
Downloads from all over the World
30.000+
Team Members' Citations in Scientific Papers
100+
Presentations at International Conferences
The YUIMA Software
The YUIMA Software 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. It 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 YUIMA Team
The YUIMA Team is mainly composed by mathematicians and statisticians who actively publish in the field of inference and simulation for Stochastic Differential Equations.
The YUIMA News
YSS2019: Computational and Statistical Methods for Stochastic Process
The first YUIMA Summer School on Computational and Statistical Methods for Stochastic Process This 4 days course aims at introducing researchers, PhD students and practitioners to several aspects of numerical and statistical analysis of time series…
Simulation and Inference for Stochastic Processes with YUIMA
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 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…
On CARMA estimation in YUIMA
Q: Can YUIMA manage with statistical inference the following model? # yuima.model object model <- setModel(drift = c("-3*x1","x1*x2"), diffusion = matrix(c("1","0"),2,1), state.variable = c("x1","x2"),…
acknowledgements
The Project has been funded up to 2010 by the Japan Science Technology (JST) Basic Research Programs PRESTO, Grants-in-Aid for Scientific Research No. 19340021. Presently, the YUIMA Project is supported by the Japan Science and Technology Agency CREST.