time series analysis by empirical mode decomposition

Empirical mode decomposition (emd) is a data-adaptive method thatprovides an approach for decomposing a time series. because of its robustness in thepresence of non-linearity and non-stationarity, emd has received much attention in thepast decade and has been used in various fields. emd decomposes a time series intosub-series called intrinsic mode functions (imfs) according to the levels of its local oscillationor frequency. this technique automatically extracts oscillations embedded ina time series and efficiently captures non-linear features with respect to amplitude andfrequency modulation at local time scale. the aim of this paper is to briefly introduceemd to researchers interested in time series analyses. using the r package emd,we demonstrate promising potentials of emd for non-stationary time series providedthrough a real-world data set. this paper is supplemented with accompanying r codes.