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Simulation and Inference for Stochastic Processes with YUIMA
Af: Nakahiro Yoshida, Stefano M. Iacus Engelsk Paperback
SPAR
kr 181
Simulation and Inference for Stochastic Processes with YUIMA
Af: Nakahiro Yoshida, Stefano M. Iacus Engelsk Paperback
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.

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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.

Produktdetaljer
Sprog: Engelsk
Sider: 268
ISBN-13: 9783319555676
Indbinding: Paperback
Udgave:
ISBN-10: 3319555677
Udg. Dato: 12 jun 2018
Længde: 19mm
Bredde: 160mm
Højde: 238mm
Oplagsdato: 12 jun 2018
Forfatter(e) Nakahiro Yoshida, Stefano M. Iacus


Kategori Matematik til informatikfag


Sprog Engelsk


Indbinding Paperback


Sider 268


Udgave


Længde 19mm


Bredde 160mm


Højde 238mm

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