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Nonlinear time series analysis with R
In the process of data analysis, the investigator is often facing highly-volatile and random-appearing observed data. A vast body of literature shows that the assumption of underlying stochastic processes was not necessarily representing the nature of the processes under investigation and, when othe...
Autores principales: | , , |
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Lenguaje: | eng |
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Oxford University Press
2017
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Acceso en línea: | https://dx.doi.org/10.1093/oso/9780198782933.001.0001 http://cds.cern.ch/record/2310557 |