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Nonlinear Time Series Analysis with R

Ray Huffaker, Marco Bittelli, and Rodolfo Rosa

Abstract

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 other tools were used, deterministic features emerged. Non Linear Time Series Analysis (NLTS) allows researchers to test whether observed volatility conceals systematic non linear behavior, and to rigorously characterize governing dynamics. Behavioral patterns detected by non linear time series analysis ... More

Keywords: Non linear time series analysis, chaos theory, phase space reconstruction, behavioral patterns, time series, observed data

Bibliographic Information

Print publication date: 2017 Print ISBN-13: 9780198782933
Published to Oxford Scholarship Online: February 2018 DOI:10.1093/oso/9780198782933.001.0001

Authors

Affiliations are at time of print publication.

Ray Huffaker, author
Professor, Agricultural and Biological Engineering, University of Florida, USA

Marco Bittelli, author
Professor, Department of Agricultural Sciences, University of Bologna, Italy

Rodolfo Rosa, author
Professor, Department of Physics and Matter Technologies, National Research Council, Italy