Periodogram time series

A periodogram is used to identify the dominant periods (or frequencies) of a time series. This can be a helpful tool for identifying the dominant cyclical behavior in a series, particularly when the cycles are not related to the commonly encountered monthly or quarterly seasonality.

1. How does periodogram work?
2. What is periodogram of a signal?
3. What's the difference between periodogram and spectrogram?
4. What are the units of a periodogram?

How does periodogram work?

A periodogram calculates the significance of different frequencies in time-series data to identify any intrinsic periodic signals. A periodogram is similar to the Fourier Transform, but is optimized for unevenly time-sampled data, and for different shapes in periodic signals.

What is periodogram of a signal?

In signal processing, a periodogram is an estimate of the spectral density of a signal. The term was coined by Arthur Schuster in 1898. Today, the periodogram is a component of more sophisticated methods (see spectral estimation).

What's the difference between periodogram and spectrogram?

For a Periodogram , returns the computed power at each frequency as a Vector. For a Spectrogram , returns the computed power at each frequency and time bin as a Matrix. Dimensions are frequency × time.

What are the units of a periodogram?

[Pxx,f] = periodogram(x,window,nfft,fs) uses the sampling frequency fs specified as an integer in hertz (Hz) to compute the PSD vector ( Pxx ) and the corresponding vector of frequencies (f). In this case, the units for the frequency vector are in Hz.