The 9th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics 2016) will take place at the Higher Technical School of Engineering (map), University of Seville, Spain, 9-11 December 2016. Tutorials will be given on Thursday 8th of December 2016.
This conference is organized by the ERCIM Working Group on Computational and Methodological Statistics (CMStatistics), University of Seville, Queen Mary University of London and Birkbeck University of 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.
The Conference will take place jointly with the 10th International Conference on Computational and Financial Econometrics (CFE 2016). The conference has a high reputation of quality presentations. The last editions of the joint conference CFE-CMStatistics gathered about 1700 participants.
All topics within the Aims and Scope of the ERCIM Working Group CMStatisticswill be considered for oral and poster presentation.
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 Yuima package will be presented. It is 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 includes 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. Stefano Iacus
Authors. Stefano Iacus, Emanuele Guidotti, Lorenzo Mercuri
Stefano Iacus
Full professor of statistics the Department of Economics, Management and Quantitative Methods at the University of Milan. Member of the R Core Team (1999-2014) for the development of the R statistical environment and now member of the R Foundation. Research interests include inference for stochastic processes, simulation, computational statistics, causal inference, text mining, and sentiment analysis.
Emanuele Guidotti
Graduated in Physics (2015) and in Quantitative Finance (2017), both with honors at the University of Milan. Teaching assistant for course "Mathematics" at the Department of Social and Political Sciences. Now partner of AlgoFinance Sagl, software house start-up developing financial algorithms for the asset management industry, and Founder of the innovative start-up WhatsOut Srl, web application enhanced by AI. Developer of the yuimaGUI.
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