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Simulation and Inference for Stochastic Processes with YUIMA - Stefano M. Iacus
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Simulation and Inference for Stochastic Processes with YUIMA - Livres de poche

2012, ISBN: 9783319555676

[ED: Taschenbuch], [PU: Springer-Verlag GmbH], Neuware - The YUIMA package is the first comprehensive R framework based on S4 classes and methods which allows for the simulation of stocha… Plus…

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Simulation and Inference for Stochastic Processes with YUIMA - Livres de poche

2012

ISBN: 9783319555676

[ED: Taschenbuch], [PU: Springer-Verlag GmbH], Neuware - The YUIMA package is the first comprehensive R framework based on S4 classes and methods which allows for the simulation of stocha… Plus…

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Simulation and Inference for Stochastic Processes with YUIMA | A Comprehensive R Framework for SDEs and Other Stochastic Processes | Stefano M. Iacus (u. a.) | Taschenbuch | Use R! | XIII | Englisch - Iacus, Stefano M.
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Simulation and Inference for Stochastic Processes with YUIMA | A Comprehensive R Framework for SDEs and Other Stochastic Processes | Stefano M. Iacus (u. a.) | Taschenbuch | Use R! | XIII | Englisch - Livres de poche

2018, ISBN: 9783319555676

[ED: Taschenbuch], [PU: Springer-Verlag GmbH], The YUIMA package is the first comprehensive R framework based on S4 classes and methods which allows for the simulation of stochastic diffe… Plus…

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Simulation and Inference for Stochastic Processes with YUIMA / A Comprehensive R Framework for SDEs and Other Stochastic Processes / Stefano M. Iacus (u. a.) / Taschenbuch / Use R! / XIII / Englisch - Iacus, Stefano M.
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Simulation and Inference for Stochastic Processes with YUIMA / A Comprehensive R Framework for SDEs and Other Stochastic Processes / Stefano M. Iacus (u. a.) / Taschenbuch / Use R! / XIII / Englisch - Livres de poche

2018, ISBN: 9783319555676

[ED: Taschenbuch], [PU: Springer-Verlag GmbH], The YUIMA package is the first comprehensive R framework based on S4 classes and methods which allows for the simulation of stochastic diffe… Plus…

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Simulation and Inference for Stochastic Processes with YUIMA

The YUIMA package is the first comprehensive R framework based on S4 classes and methods which allows for the simulation of stochastic differential equations driven by Wiener process, Lévy processes or fractional Brownian motion, as well as CARMA, COGARCH, and Point processes. The package 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. YUIMA 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 book explains briefly the underlying theory for simulation and inference of several classes of stochastic processes and then presents both simulation experiments and applications to real data. Although these processes have been originally proposed in physics and more recently in finance, they are becoming popular also in biology due to the fact the time course experimental data are now available. The YUIMA package, available on CRAN, can be freely downloaded and this companion book will make the user able to start his or her analysis from the first page.

Informations détaillées sur le livre - Simulation and Inference for Stochastic Processes with YUIMA


EAN (ISBN-13): 9783319555676
ISBN (ISBN-10): 3319555677
Livre de poche
Date de parution: 2017
Editeur: Springer International Publishing

Livre dans la base de données depuis 2017-04-05T11:00:56+02:00 (Zurich)
Page de détail modifiée en dernier sur 2024-03-01T08:38:31+01:00 (Zurich)
ISBN/EAN: 9783319555676

ISBN - Autres types d'écriture:
3-319-55567-7, 978-3-319-55567-6
Autres types d'écriture et termes associés:
Auteur du livre: iacus, malliavin, yoshida, stefano
Titre du livre: simulation, stefano


Données de l'éditeur

Auteur: Stefano M. Iacus; Nakahiro Yoshida
Titre: Use R! Simulation and Inference for Stochastic Processes with YUIMA - A Comprehensive R Framework for SDEs and Other Stochastic Processes
Editeur: Springer; Springer International Publishing
268 Pages
Date de parution: 2018-06-12
Cham; CH
Imprimé / Fabriqué en
Langue: Anglais
69,54 € (DE)
71,49 € (AT)
77,00 CHF (CH)
POD
XIII, 268 p. 83 illus., 32 illus. in color.

BC; Hardcover, Softcover / Mathematik/Wahrscheinlichkeitstheorie, Stochastik, Mathematische Statistik; Wahrscheinlichkeitsrechnung und Statistik; Verstehen; Lévy processes; R language; YUIMA; computational statistics; simulation and inference for stochastic processes; stochastic differential equations; levy; Malliavin calculus; CRAN; Brownian motion; Wiener process; CARMA; COGARCH; quasi maximum likelihood estimation; adaptive Bayes estimation; structural change point analysis; hypotheses testing; asynchronous covariance estimation; lead-lag estimation; LASSO model selection; Statistics and Computing; Probability and Statistics in Computer Science; Probability Theory; Mathematische und statistische Software; Mathematik für Informatiker; Stochastik; EA

1 Introduction.- 2 Diffusion processes.- 3 Compound Poisson processes.- 4 Stochastic differential equations driven by Lévy processes.- 5 Stochastic differential equations driven by the fractional Brownian motion.- 6 CARMA models.- 7 COGARCH models.- Reference.- Index.

, is full professor of statistics in the Department of Economics, Management and Quantitative Methods at the University of Milan. He has been a member of the R Core Team (1999-2014) for the development of the R statistical environment and is now a member of the R Foundation. His research interests include inference for stochastic processes, simulation, computational statistics, causal inference, text mining, and sentiment analysis.

 is full professor at the Graduate School of Mathematical Sciences, University of Tokyo. He is working in theoretical statistics, probability theory, computational statistics, and financial data analysis. He was awarded the Japan Statistical Society Award in 2009 and the Analysis Prize from the Mathematical Society of Japan in 2006.

Stefano M. Iacus, PhD Nakahiro Yoshida, PhD,

, is full professor of statistics the Department of Economics, Management and Quantitative Methods at the University of Milan. He has been a member of the RCore Team (1999-2014) for the development of the R statistical environment and now member of the R Foundation. His research interests include inference for stochastic processes, simulation, computational statistics, causal inference, text mining, and sentiment analysis. 

 is a professor at the Graduate School of Mathematical Sciences, University of Tokyo. He is working in theoretical statistics, probability theory, computational statistics, and financial data analysis. He was awarded the Japan Statistical Society Award in 2009 and the Analysis Prize from the Mathematical Society of Japan in 2006.

Stefano M. Iacus, PhD Nakahiro Yoshida, PhD,
Contains both theory and R code with step-by-step examples and figures Uses YUIMA package to implement the latest techniques available in the literature of inference and simulation for stochastic processes Shows how to create the description of very abstract models in the same way they are described in theoretical papers but with an extremely easy interface

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