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Published in:
2017 | OriginalPaper | Chapter
Tests for Serial Independence
Author : Jan G. De Gooijer
Published in: Elements of Nonlinear Time Series Analysis and Forecasting
Publisher: Springer International Publishing
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Testing for randomness of a given finite time series is one of the basic problems of statistical analysis. For instance, in many time series models the noise process is assumed to consist of i.i.d. random variables, and this hypothesis should be testable. Also, it is the first issue that gets raised when checking the adequacy of a fitted time series model through observed “residuals”, i.e. are they approximately i.i.d. or are there significant deviations from that assumption. In fact, many inference procedures apply only to i.i.d. processes.