BicAn: An integrated, open-source framework for polyspectral analysis

Description

We present a novel platform for higher-order spectral analysis of time series data in Python. The theory, utility, and applications of such analyses are summarized. Direct estimation of coherence (n = 2), bicoherence (n = 3), and tricoherence (n = 4) spectra are given for test signals; higher-order (n > 4) spectra are inferred at single points in polyfrequency space. Quantification of uncertainty for nonstationary processes is considered, and applications to nonlinear dynamics research are given.

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