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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 - edizione con copertina flessibile

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… Altro …

Costi di spedizione:Versandkostenfrei, Versand nach Deutschland. (EUR 0.00) Buchhandlung Hoffmann
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Simulation and Inference for Stochastic Processes with YUIMA - Stefano M. Iacus
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Stefano M. Iacus:

Simulation and Inference for Stochastic Processes with YUIMA - edizione con copertina flessibile

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… Altro …

Costi di spedizione:Versandkostenfrei, Versand nach Deutschland. (EUR 0.00) Mein Buchshop
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Simulation and Inference for Stochastic Processes with YUIMA - Stefano M. Iacus
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Stefano M. Iacus:
Simulation and Inference for Stochastic Processes with YUIMA - edizione con copertina flessibile

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… Altro …

Costi di spedizione:Versandkostenfrei, Versand nach Deutschland. (EUR 0.00) buchversandmimpf2000
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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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Iacus, Stefano M.:
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 - edizione con copertina flessibile

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… Altro …

Costi di spedizione:Versandkostenfrei, Versand nach Deutschland. (EUR 0.00) preigu
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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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Iacus, Stefano M.:
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 - edizione con copertina flessibile

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… Altro …

Costi di spedizione:Versandkostenfrei, Versand nach Deutschland. (EUR 0.00) MEOVERSA

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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.

Informazioni dettagliate del libro - Simulation and Inference for Stochastic Processes with YUIMA


EAN (ISBN-13): 9783319555676
ISBN (ISBN-10): 3319555677
Copertina flessibile
Anno di pubblicazione: 2017
Editore: Springer International Publishing

Libro nella banca dati dal 2017-04-05T11:00:56+02:00 (Zurich)
Pagina di dettaglio ultima modifica in 2024-03-01T08:38:31+01:00 (Zurich)
ISBN/EAN: 9783319555676

ISBN - Stili di scrittura alternativi:
3-319-55567-7, 978-3-319-55567-6
Stili di scrittura alternativi e concetti di ricerca simili:
Autore del libro : iacus, malliavin, yoshida, stefano
Titolo del libro: simulation, stefano


Dati dell'editore

Autore: Stefano M. Iacus; Nakahiro Yoshida
Titolo: Use R! Simulation and Inference for Stochastic Processes with YUIMA - A Comprehensive R Framework for SDEs and Other Stochastic Processes
Editore: Springer; Springer International Publishing
268 Pagine
Anno di pubblicazione: 2018-06-12
Cham; CH
Stampato / Fatto in
Lingua: Inglese
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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