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The periodogram, while useful for identifying periodic signals in data, has several demerits. Firstly, it can suffer from high variance, leading to unreliable spectral estimates, especially with short time series. Additionally, it may not effectively distinguish between closely spaced frequencies, resulting in spectral leakage. Lastly, the periodogram assumes stationarity, which can be a limitation when analyzing non-stationary data.

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