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"The book describes main statistical procedures used in modern nonlinear time series analysis. ... Each chapter ends with a section containing various exercises, both theoretical and simulation, which makes the book suitable for a graduate course in nonlinear time series. Each chapter also contains a section with useful information about the existing software (mainly in MATLAB and R) related to the topic of the chapter." (Vytautas Kazakevicius, Mathematical Reviews, January, 2018)
"This is an excellent addition to the library of books on time series analysis. The most attractive feature of this book is that it places importance on developing intuition about nonlinear time series rather than the more formal theorem-proof approach. It is abundant with data examples and simulations that enhance understanding of the stochastic properties of the models. In my opinion, the approach taken is the best pedagogical technique to learn about time series models." (Hernando Ombao, Journal of the American Statistical Association JASA, Vol. 113 (522), 2018)

"For the scientific quality of its content I do not exaggerate if I consider this book as a treasure." (Oscar Busto, zbMATH 1376.62001, 2018)