Simulation and Inference for Stochastic Processes with YUIMA : A Comprehensive R Framework for SDEs and Other Stochastic Processes. 1st ed. 2018

種類:

電子ブック

責任表示:

by Stefano M. Iacus, Nakahiro Yoshida

出版情報:

Cham : Springer International Publishing : Imprint: Springer, 2018

著者名:

• Iacus, Stefano M.
• Yoshida, Nakahiro.
• SpringerLink (Online service)

シリーズ名:

Use R! ;

ISBN:

9783319555690 [3319555693]    

注記:

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.
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 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 pro

ローカル注記:

学内専用E-BOOKS (local access only)