I presented The Yuima framework for simulation and inference of stochastic processes and its GUI at the 10th International Conference of the ERCIM WG on Computational and Methodological Statistics, London.
This conference is organized by the ERCIM Working Group on Computational and Methodological Statistics (CMStatistics), Birkbeck University of London and King’s College London. The new journal Econometrics and Statistics (EcoSta)and its supplement, the Annals of Computational and Financial Econometrics are the main sponsors of the conference. The journals Econometrics and Statistics and Computational Statistics & Data Analysis publishes selected papers in special peer-reviewed, or regular issues.
Topics includes, but not limited to: robust methods, statistical algorithms and software, high-dimensional data analysis, statistics for imprecise data, extreme value modeling, quantile regression and semiparametric methods, model validation, functional data analysis, Bayesian methods, optimization heuristics in estimation and modelling, computational econometrics, quantitative finance, statistical signal extraction and filtering, small area estimation, latent variable and structural equation models, mixture models, matrix computations in statistics, time series modeling and computation, optimal design algorithms and computational statistics for clinical research.
The Yuima framework for simulation and inference of stochastic processes and its GUI
Abstract. The purpose is to present the Yuima package, a system of S4 classes and methods for the simulation and inference of stochastic processes including stochastic differential equation with or without jumps, fractional Brownian motion, Poisson and general point processes, CARMA and COGARCH processes. Yuima is a collaborative project and includes several simulation schemes as well statistical tools for quasi-maximum likelihood estimation, model selection, hypotheses testing, change point analysis. It also include methods of asymptotic expansion. Recently, the Yuima package has been coupled with a graphical user interface, namely the YuimaGUI, which simplifies the usage of the package and allows for a complete flow of analysis: from data ingestion, to model selection and or estimation, and estimation.
Speaker. Emanuele Guidotti
Authors. Emanuele Guidotti, Stefano Iacus, Lorenzo Mercuri