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===Recurrence quantification analysis=== [[Recurrence quantification analysis]] has been employed to detect the characteristic of business cycles and [[economic development]]. To this end, Orlando et al.<ref>{{cite journal |last1=Orlando |first1=Giuseppe |last2=Zimatore |first2=Giovanna |title=RQA correlations on real business cycles time series |journal=Indian Academy of Sciences β Conference Series |date=18 December 2017 |volume=1 |issue=1 |pages=35β41 |doi=10.29195/iascs.01.01.0009|doi-access=free }}</ref> developed the so-called recurrence quantification correlation index to test correlations of RQA on a sample signal and then investigated the application to business time series. The said index has been proven to detect hidden changes in time series. Further, Orlando et al.,<ref name="sciencedirect.com">{{cite journal |last1=Orlando |first1=Giuseppe |last2=Zimatore |first2=Giovanna |title=Recurrence quantification analysis of business cycles |journal=Chaos, Solitons & Fractals |date=1 May 2018 |volume=110 |pages=82β94 |doi=10.1016/j.chaos.2018.02.032 |bibcode=2018CSF...110...82O |s2cid=85526993 |url=https://www.sciencedirect.com/science/article/abs/pii/S0960077918300924 |language=en |issn=0960-0779}}</ref> over an extensive dataset, shown that recurrence quantification analysis may help in anticipating transitions from laminar (i.e. regular) to turbulent (i.e. chaotic) phases such as USA GDP in 1949, 1953, etc. Last but not least, it has been demonstrated that recurrence quantification analysis can detect differences between macroeconomic variables and highlight hidden features of economic dynamics.<ref name="sciencedirect.com"/>
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