A new method to compare the spectral densities of two independent periodically correlated time series

Abstract In some situations, for example in signal processing, economics, electronic, finance, and climatology, researchers wish to determine whether the two time series are generated by the same stochastic mechanism or their random behavior differs. In this work, the asymptotic distribution for the discrete Fourier transform of periodically correlated time series is applied to derive hypothesis testing for the equality of two periodically correlated time series. Then the Monte Carlo simulation study is provided to investigate the performance of proposed method.

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