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Titlebook: Elements of Nonlinear Time Series Analysis and Forecasting; Jan G. De Gooijer Book 2017 Springer International Publishing Switzerland 2017

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Frequency-Domain Tests,d abandon it only if sufficiently strong evidence for a nonlinear alternative can be found. This approach can be applied using a linearity test, often in combination with a test for Gaussianity. Several test statistics, both in the time domain and frequency domain, have been proposed for this purpose.
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Management von Franchisenetzwerkenodeling the dynamic relationship of a time series, obtaining its characteristic features, forecasting future occurrences, and hypothesizing marginal statistics. Our concern is with time series that occur in discrete time and are realizations of a stochastic/random process.
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Book 2017thms and real-world applications. Avoiding a “theorem-proof” format, it shows concrete applications on a variety of empirical time series. The book can be used in graduate courses in nonlinear time series and at the same time also includes interesting material for more advanced readers. Though it is
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Gesunde Unternehmen in der Zugspitz-Region, 11, we deal with vector (multivariate) parametric models in which there are several jointly dependent time series variables. Nonparametric univariate and multivariate methods will be the focus of Chapters 4, 9 and 12.
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Classic Nonlinear Models, 11, we deal with vector (multivariate) parametric models in which there are several jointly dependent time series variables. Nonparametric univariate and multivariate methods will be the focus of Chapters 4, 9 and 12.
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