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Abstract:
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Manny Parzen was a longstanding proponent of using cepstral models and advocated for their use in several contexts. Although the original model was formulated as the Fourier transform of the log spectral density of a scalar time series, the model has recently been extended in several directions, including random fields, seasonal long memory time series, multivariate time series, and nonstationary time series, among others. This talk describes the impact of Manny Parzen's vision by providing an overview of recent advances made in the area of cepstral models along with illustrating many of the associated applications.
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