By Jan G. De Gooijer
This ebook offers an outline of the present cutting-edge of nonlinear time sequence analysis, richly illustrated with examples, pseudocode algorithms and real-world functions. averting a “theorem-proof” structure, it exhibits concrete functions on a number of empirical time sequence. The book can be utilized in graduate classes in nonlinear time sequence and whilst additionally includes interesting fabric for extra complicated readers. notwithstanding it's mostly self-contained, readers require an figuring out of simple linear time sequence strategies, Markov chains and Monte Carlo simulation methods.
The e-book covers time-domain and frequency-domain equipment for the research of either univariate and multivariate (vector) time sequence. It makes a transparent contrast among parametric types at the one hand, and semi- and nonparametric models/methods at the different. this provides the reader the choice of concentrating completely on the sort of nonlinear time sequence research methods.
To make the publication as person pleasant as attainable, significant aiding options and really good tables are appended on the finish of every bankruptcy. additionally, each one bankruptcy concludes with a collection of key phrases and ideas, in addition to a precis of the most findings. finally, the ebook deals various theoretical and empirical workouts, with solutions supplied through the writer in an intensive suggestions manual.
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Extra resources for Elements of Nonlinear Time Series Analysis and Forecasting (Springer Series in Statistics)
Elements of Nonlinear Time Series Analysis and Forecasting (Springer Series in Statistics) by Jan G. De Gooijer