Abstract
Time-series analysis aims to investigate the temporal behavior of a variable x(t). Examples include the investigation of long-term records of mountain uplift, sea-level fluctuations, orbitally-induced insolation variations and their influence on the ice-age cycles, millennium-scale variations in the atmosphere-ocean system, the effect of the El Nino/Southern Oscillation on tropical rainfall and sedimentation (Fig. 5.1), and tidal influences on noble gas emissions from bore holes. The temporal pattern of a sequence of events can be random, clustered, cyclic, or chaotic. Time-series analysis provides various tools with which to detect these temporal patterns. Understanding the underlying processes that produced the observed data allows us to predict future values of the variable.
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Trauth, M.H. (2015). Time-Series Analysis. In: MATLAB® Recipes for Earth Sciences. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-46244-7_5
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